
#import dependencies
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
import helpers
import matplotlib.dates as mdates
import plotly.express as px
import plotly.graph_objects as go
import re
import warnings
warnings.filterwarnings('ignore')
sb.set_style("darkgrid")
%matplotlib inline


# load data
df = pd.read_csv("cleaned_data/reddit_cleaned_2021.csv")
df_merged = pd.read_csv("cleaned_data/reddit_merged_2021.csv")

df_users = pd.read_csv("cleaned_data/users_cleaned.csv")


# convert to datetime
df.created_at = pd.to_datetime(df.created_at)
df_merged.created_at = pd.to_datetime(df_merged.created_at)
df_merged.user_created_at = pd.to_datetime(df_merged.user_created_at)
df_users.user_created_at = pd.to_datetime(df_users.user_created_at)


px.bar(data_frame=df['submission_comment'].value_counts().to_frame().reset_index(),
       x="index", y="submission_comment", color='submission_comment').update_layout(title='Comment or Submission',
                   xaxis_title='contribution category',
                   yaxis_title='number of contributions').update_traces(marker_color='#5296dd')


df.author.value_counts().to_frame().head(10).reset_index()


fig = px.bar(df.author.value_counts().to_frame().head(10).reset_index(), x="author", y="index",
             height=500,
             title='Most commented user in 2021').update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='number of comments',
                   yaxis_title='user name').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


df.author.value_counts().to_frame().head(10).reset_index()


df_auto_moderator = df.query(" author == 'AutoModerator' ").reset_index(drop=True)
print(df_auto_moderator.shape)
df_auto_moderator.head(1)

(515, 17)


df_auto_moderator.subreddit.value_counts().head(10)

r/JerkOffToCelebs         176
r/memes                    55
r/Celebhub                 48
r/unpopularopinion         32
r/AskReddit                30
r/DC_Cinematic             26
r/CelebBattleLeague        22
r/OutOfTheLoop             18
r/iamatotalpieceofshit     17
r/jerkbudss                 6
Name: subreddit, dtype: int64


df_auto_moderator['permalink'].iloc[26]

'/r/darkjokes/comments/kq9r9d/if_relationship_of_amber_heard_and_johnny_depp/gi2itdv/'


df_auto_moderator.text.value_counts().head();


df_vote_bot = df.query(" author == 'CelebBattleVoteBot' ").reset_index(drop=True)
print(df_vote_bot.shape)
df_vote_bot.head()

(163, 17)


df_vote_bot['permalink'].iloc[0]

'/r/CelebbattlePolls/comments/ko1ew0/marvel_vs_dc_team_marvel_evangeline_lilly_brie/'


df_vote_bot.subreddit.value_counts().head(10)

r/CelebbattlePolls    83
r/CelebBattles        79
r/JerkOffToCelebs      1
Name: subreddit, dtype: int64


df_vote_bot.text.value_counts().head()

Amanda Seyfried VS. Amber Heard                                                                        2
Anne Hathaway vs Amber Heard                                                                           2
Poll for [Amber Heard vs Torrie Wilson](https://reddit.com/lp7af8) on CelebBattles                     1
Poll for [Katy Perry vs Evangeline Lilly vs Amber Heard](https://reddit.com/l3eo1l) on CelebBattles    1
Poll for [Zoe Saldana vs Amber Heard](https://reddit.com/n958ue) on CelebBattles                       1
Name: text, dtype: int64


df_charliedba = df.query(" author == 'charliedba' ").reset_index(drop=True)
print(df_charliedba.shape)
df_charliedba.head()

(99, 17)


df_charliedba['permalink'].iloc[0]

'/r/Amber_Heard/comments/ms8xkq/long_legged_beauty_amber_heard/'


df_charliedba.subreddit.value_counts().head(10)

r/Amber_Heard_2       80
r/Amber_Heard          7
r/HighResCelebs        3
r/UHQcelebs            3
r/BeautifulFemales     2
r/Celebhub             1
r/PrettyWomen          1
r/Celebs               1
r/FamousFaces          1
Name: subreddit, dtype: int64


df_charliedba.text.value_counts().head(10)

Amber Heard                  31
Stunning Amber Heard          4
Cute Amber Heard              3
Amber Heard [2100 x 3150]     3
Gorgeous Amber Heard          3
Angelic Amber Heard           3
Amber Heard [irtr]            2
Young Amber Heard             2
Amber Heard [2218 x 3000]     2
Amber Heard collage           2
Name: text, dtype: int64


# check the date this account was creted

# user_name --> index
# at[index_value , 'column']
# df_users.set_index('user_name').at['Stanley_Elkind', 'user_created_at']

df_users[df_users.user_name == 'Stanley_Elkind']


df_stanley = df.query(" author == 'Stanley_Elkind' ").reset_index(drop=True)
print(df_stanley.shape)
df_stanley.head()

(44, 17)


df_stanley.subreddit.value_counts().head(10)

r/JerkOffToCelebs        36
r/pickoneceleb            3
r/CelebAssPussyMouth      2
r/CelebWouldYouRather     2
r/DC_Cinematic            1
Name: subreddit, dtype: int64


df_stanley.text.value_counts().head(10)

When it comes to Amber Heard I let my penis make the decisions.                                                                                                                                                                                                                                                                                                               1
Honestly, the more people tell she’s evil the more I want to cum for her                                                                                                                                                                                                                                                                                                      1
Black widow                                                                                                                                                                                                                                                                                                                                                                   1
I’d like Amber all to myself. I’d like to try double anal with Margot.                                                                                                                                                                                                                                                                                                        1
Squeeze Emily’s fat ass while she’s riding me\n\nStuff my genitals inside Bella’s face \n\nFully clothed handjob with Florence. Her sultry eyes are more than enough for me. \n\nOily titjob from Lizzie Olsen and cum inside her pretty mouth\n\nRough doggy style anal with Amber Heard for obvious reasons\n\nMake out with Zendaya until it leaves a stain in my pants    1
[Morgan Freeman voice]\n\nI agree with the second part.                                                                                                                                                                                                                                                                                                                       1
I don’t actually care what she did. The hate lobbed at her is just different type of celebrity worship which Reddit supposedly hates. I like to cum to pics of her face.                                                                                                                                                                                                      1
I gotta admit... i would lick her shitter                                                                                                                                                                                                                                                                                                                                     1
Everyone is cool burgeoning cult leader Jared Leto though.                                                                                                                                                                                                                                                                                                                    1
Breed repeatedly on my own: Gal\n\nBreed once: Melissa\n\nGang bang Margot\n\nAnd this was obviously just an excuse to hear other people say theyd watch Amber Heard get fucked by a horse                                                                                                                                                                                    1
Name: text, dtype: int64


df_stanley_contributions = df_stanley.groupby(df_stanley.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_stanley_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Stanley_Elkind" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_stanley_contributions.created_at,
    )
)

fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


# check the date this account was creted
df_users[df_users.user_name == 'Truthbetheprejudice']


df_truth = df.query(" author == 'Truthbetheprejudice' ").reset_index(drop=True)
print(df_truth.shape)
df_truth.head()

(43, 17)


df_truth.subreddit.value_counts().head(10)

r/entertainment           10
r/MensRights              10
r/movies                  10
r/pussypassdenied          8
r/JusticeForJohnnyDepp     5
Name: subreddit, dtype: int64


df_truth.text.value_counts().head(10)

Johnny Depp sues ACLU on to see if ex-wife Amber Heard gave $7m divorce settlement                                                      5
Amber Heard Is Allegedly Being Investigated By LAPD For Perjury, Could Face Jail Time Over Johnny Depp Domestic Violence Accusations    5
Amber Heard probed for perjury and staging 2016 Johnny Depp domestic violence case: 'Lock her up'                                       5
Amber Heard Under Investigation for Perjury in Johnny Depp Domestic Violence Case                                                       5
Amber Heard to struggle in new LAPD domestic violence probe                                                                             5
#JusticeForJohnnyDepp Johnny Depp fans donate $40k to children that Amber Heard neglected                                               4
Remove Amber Heard from Aquaman 2                                                                                                       4
Confirmed: Amber Heard Under Criminal Investigation in Australia                                                                        4
Big tech silence Johnny Depp and censor Amber Heard evidence                                                                            3
Johnny Depp Makes an Appearance in Spain as Lawyers Drop New Evidence in Amber Heard Case                                               2
Name: text, dtype: int64


df_truth_contributions = df_truth.groupby(df_truth.created_at.dt.date).size().reset_index(name='n_contributions')
df_truth_contributions


fig = px.bar(df_truth_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Truthbetheprejudice" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_truth_contributions.created_at,
    )
)

fig.update_traces(marker_color='red',
                  marker_line_width=2, opacity=1, textposition='auto')
fig.show()


df_gaul = df.query(" author == 'gaul66' ").reset_index(drop=True)
print(df_gaul.shape)
df_gaul.head()

(37, 17)


df_gaul.subreddit.value_counts().head(10)

r/CelebBattles    37
Name: subreddit, dtype: int64


df_gaul['permalink'].iloc[5]

'/r/CelebBattles/comments/l4h1wp/amber_heard_vs_brie_larson/gkpl5eg/'


# check the date this account was creted

# user_name --> index
# at[index_value , 'column']
# df_users.set_index('user_name').at['Stanley_Elkind', 'user_created_at']

df_users[df_users.user_name == 'LoveAmberHeard42286']


df_love = df.query(" author == 'LoveAmberHeard42286' ").reset_index(drop=True)
print(df_love.shape)
df_love.head()

(124, 17)


df_love.subreddit.value_counts().head(10)

r/JerkOffToCelebs         85
r/Celebhub                26
r/gentlemanboners          4
r/unpopularopinion         2
u/LoveAmberHeard42286      2
r/Celebrityfemdom          1
r/Celebs                   1
r/Amber_Heard              1
r/IStandWithAmberHeard     1
r/celebgifs                1
Name: subreddit, dtype: int64


df_love.text.value_counts().head(10)

Amber Heard                                                                                                                                                                                     72
Amber Heard 💜                                                                                                                                                                                    6
Amber Heard ❤                                                                                                                                                                                    5
She's an abuse victim as multiple judges have agreed on based on evidence. And what you're talking about is rape. You need to take a look at yourself before casting stones at someone else.     2
Didn't do anything wrong? That must he why he lost his case.                                                                                                                                     1
The only trash is Her wino ex husband. Fuck that loser.                                                                                                                                          1
i love me some Amber Heard                                                                                                                                                                       1
Maybe he should have tried to not be an abusive crackhead                                                                                                                                        1
... 5 months later. Looks like the sun wasn't lying for once.                                                                                                                                    1
Go jump back up your mother and cook some more, retard.                                                                                                                                          1
Name: text, dtype: int64


df_love_contributions = df_love.groupby(df_love.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_love_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "LoveAmberHeard42286" contributions in 2021')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_stanley_contributions.created_at,
    )
)

fig.update_traces(marker_color='red', marker_line_width=2, opacity=1) 
# , marker_line_color='#5296dd'

fig.show()


df_love_contributions.sort_values('n_contributions', ascending=False)


# check the date this account was creted
df_users[df_users.user_name == 'sadwook']


df_sadwook = df.query(" author == 'sadwook' ").reset_index(drop=True)
print(df_sadwook.shape)
df_sadwook.head()

(32, 17)


df_sadwook.subreddit.value_counts().head(10)

r/pussypassdenied    32
Name: subreddit, dtype: int64


df_sadwook_contributions = df_sadwook.groupby(df_sadwook.created_at.dt.date).size().reset_index(name='n_contributions')
df_sadwook_contributions


fig = px.bar(df_sadwook_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "sadwook" contributions in 2021')
fig.update_traces(marker_color='red',
                  marker_line_width=2, opacity=1, textposition='auto')
fig.show()


df_sadwook_hrs = df_sadwook.groupby(df_sadwook.created_at.dt.hour).size().reset_index(name='n_contributions')
df_sadwook_hrs


fig = px.bar(df_sadwook_hrs,
             x='created_at', 
             y='n_contributions', title='The number of "sadwook" contributions in 2021')
fig.update_traces(marker_color='red', 
                  marker_line_width=2, opacity=1, textposition='auto')
fig.show()


df_beatplayer = df.query(" author == 'Beatplayer' ").reset_index(drop=True)
print(df_beatplayer.shape)
df_beatplayer.head()

(32, 17)


df_beatplayer['permalink'].iloc[0]

'/r/TrueOffMyChest/comments/lx2s7w/its_disgusting_that_people_are_less_angry_about/gpl1ocz/'


df_beatplayer.subreddit.value_counts().head(10)

r/TrueOffMyChest    32
Name: subreddit, dtype: int64


df_beatplayer.text.value_counts().head(3)

So it’s nearly 12 and I’ll be back tomorrow to read this :) Sleep well!                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     1
I’m not sure that the case to be honest. \n\nIt was proven in a court, on the balance of probabilities, that a media outlet was justified in calling JD domestically abusive. They couldn’t say the same for me, for instance, because I’m not domestically abusive. \n\nSimilarly in the civil case, there were a number of preliminary rulings that found, on the balance of probabilities, that there was enough evidence of abuse to out protective measures in place. Again, the same couldn’t be said for me for instance, because there is no evidence of abusing behaviour. He then, quite sensibly settled. Ya know, because he would have lost. Because of the evidence. \n\nIt’s reaching a little bit to say that he hasn’t lost a case. Although I see roughly where you’re coming from. \n\nI suspect it would be manifestly a bad move for him to sue her. Is that happening?                                                                                                                                                                                                1
‘Obviously, most domestic abuse is committed by men’ \n\n- what makes it obvious? Is it that DV is a male problem, and you just don’t like seeing it written in an English? \n\n‘Women can also rape men’ \n- No no, they genuinely can’t. They can be secondaries to a crime of rape (and interestingly, women who are convicted of any type of sexual or violent crime are, almost without exception, secondaries to a male perpetrator) but they absolutely cannot be rapists. Unless you’re making a very forward thinking point about the trans community. Which I absolutely don’t think you are. \n\nTo be honest, if I was a big ole manly testosterone driven drug addled abuser, I’d be petrified of a women who was brave enough to document my behaviour. I’d probably release all sorts of unevidenced wank to the media, which would probably be lapped up by a wide range of misogynist internet commenters. I’d probably be fairly successful in it. And I’d also probably be cognisant that that was part of the spectrum of abuse I was putting my ex-partner through.    1
Name: text, dtype: int64


df.author.value_counts().nlargest(n=25)

-banned-                1587
AutoModerator            515
CelebBattleVoteBot       163
LoveAmberHeard42286      124
charliedba                99
Stanley_Elkind            44
Truthbetheprejudice       43
gaul66                    37
Beatplayer                32
sadwook                   32
AltruisticVariation4      31
YahYah241                 31
faithle55                 30
amphibiousParakeet        29
Jreal22                   28
BalonSwann07              26
masseffect2001            25
Thankunext4               25
DutchArtworks             24
swampwitch116             24
EdwardCircumcizehand      24
Aphaelo                   23
cptn3sm10                 23
the-speed-of-pain         22
my_alt_account1312        22
Name: author, dtype: int64


check_list = df.author.value_counts().nlargest(n=25).index.tolist()[1:]
check_list

['AutoModerator',
 'CelebBattleVoteBot',
 'LoveAmberHeard42286',
 'charliedba',
 'Stanley_Elkind',
 'Truthbetheprejudice',
 'gaul66',
 'Beatplayer',
 'sadwook',
 'AltruisticVariation4',
 'YahYah241',
 'faithle55',
 'amphibiousParakeet',
 'Jreal22',
 'BalonSwann07',
 'masseffect2001',
 'Thankunext4',
 'DutchArtworks',
 'swampwitch116',
 'EdwardCircumcizehand',
 'Aphaelo',
 'cptn3sm10',
 'the-speed-of-pain',
 'my_alt_account1312']


# get a data frame with the most negative-comments users
df_check = df_users[df_users['user_name'].isin(check_list)]
print(df_check.shape)
df_check.head(2)

(24, 10)


df_check['user_name'].nunique()

24


for col in df_check.columns:
    if col not in ['user_name', 'user_created_at']:
        print('The value counts of the users with the most contributions: ' + col)
        print(df_check[col].value_counts())
        print('\n')

The value counts of the users with the most contributions: has_verified_email
True    24
Name: has_verified_email, dtype: int64


The value counts of the users with the most contributions: is_mod
False    14
True     10
Name: is_mod, dtype: int64


The value counts of the users with the most contributions: is_gold
False    18
True      6
Name: is_gold, dtype: int64


The value counts of the users with the most contributions: is_banned
False    20
True      4
Name: is_banned, dtype: int64


The value counts of the users with the most contributions: comment_karma
100113.0    1
146.0       1
1000.0      1
1359.0      1
16915.0     1
13977.0     1
5608.0      1
131.0       1
27642.0     1
405.0       1
25602.0     1
1916.0      1
18790.0     1
1436.0      1
22104.0     1
1206.0      1
328449.0    1
1063.0      1
17395.0     1
88814.0     1
Name: comment_karma, dtype: int64


The value counts of the users with the most contributions: link_karma
331.0      1
3388.0     1
1000.0     1
32197.0    1
30001.0    1
1127.0     1
1296.0     1
301.0      1
1138.0     1
108.0      1
482.0      1
2985.0     1
51.0       1
10931.0    1
19887.0    1
1439.0     1
21.0       1
14912.0    1
20315.0    1
1.0        1
Name: link_karma, dtype: int64


The value counts of the users with the most contributions: banned_unverified
others    20
banned     4
Name: banned_unverified, dtype: int64


The value counts of the users with the most contributions: creation_year
2019      6
2021      5
banned    4
2020      4
others    3
2018      2
Name: creation_year, dtype: int64


# pd.set_option('display.max_colwidth', None)
suspected_dict = {}


df_fuc = df[df.text.str.lower().str.contains('fuck')]
print(df_fuc.shape)
df_fuc.head()

(1227, 17)


# get the authors of these submissions having the same submission text

mask = (df['submission_text'] == 'fuck_amber_heard') & (df['submission_comment'] == 'submission')
df_sub = df[mask]
print(df_sub.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_sub.head())

(7, 17)


# get the authors of these submissions having the same submission text

mask = (df['submission_text'].str.contains('fuck')) & (df['submission_comment'] == 'submission')
df_sub_fuc = df[mask]
print(df_sub_fuc.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_sub_fuc.head())

(49, 17)


df_sub_fuc_contributions = df_sub_fuc.groupby(df_sub_fuc.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(df_sub_fuc_contributions,
             x='created_at', 
             y='n_contributions', title='The number of submissions with the word "F*CK" in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_sub_fuc_contributions.sort_values('n_contributions', ascending=False)


df_fuc.author.value_counts().head(10)

-banned-               86
Jreal22                10
Loveseeingthatsmile     6
AutoModerator           5
VampireQueenDespair     4
zephyrBoom72            4
thesecoloursdontrun     4
blackweebow             4
HornyJit                4
Stanley_Elkind          4
Name: author, dtype: int64


df_fuc.submission_comment.value_counts()

comment       1150
submission      77
Name: submission_comment, dtype: int64


df_fuc.subreddit.value_counts().head(10)

r/JerkOffToCelebs         188
r/entertainment           154
r/pussypassdenied         151
r/MensRights               82
r/TrueOffMyChest           66
r/iamatotalpieceofshit     61
r/CelebAssPussyMouth       27
r/awfuleverything          27
r/DC_Cinematic             27
r/AskReddit                26
Name: subreddit, dtype: int64


df_fuc.created_at.dt.date.value_counts().head(10)

2021-04-17    73
2021-02-28    72
2021-03-04    60
2021-05-11    45
2021-02-20    40
2021-01-16    34
2021-05-08    25
2021-04-18    25
2021-04-01    24
2021-01-01    23
Name: created_at, dtype: int64


df_fuc_contributions = df_fuc.groupby(df_fuc.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(df_fuc_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "F*CK" contributions in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_fuc_contributions.sort_values('n_contributions', ascending=False).head(10)


df_jeral = df.query(" author == 'Jreal22' ")
print(df_jeral.shape)
df_jeral.head()

(28, 17)


df_jeral.text.value_counts().head(3)

Yeah, Depp needed to stop doing the same movies, he is super talented and could have an Oscar by now easily.\n\nBut he got to making 100 million a movie and fked it up a bit.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  1
If you listen to the tapes he actually seems like a really nice guy, he tries so much to calm her down and whatnot.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             1
I dated a woman who would slap the shit out of me and beg me to hit her back. I'm like, I'm never going to hit you back, she drank, and I didn't.\n\nThen one time things started getting really weird and she stood me up one night.\n\nI was like, what's up? And she bust out crying and said her dad had died.\n\nI felt terrible, so I was real nice to her that week, then I told my mom just in normal convo that her dad had died, so my mom called her mom to send her condolences for my girlfriends dad dying.\n\nGuess who's dad didn't die?\n\nThat's right, the girl was cheating on me and she forgot about dinner because she was sleeping with another guy, so she made up a lie THAT HER DAD WAS DEAD just to get out of why she stood me up for dinner.\n\nI called her mom and told her what she did and that I would no longer be dating her and that I was very sorry, but that I wanted to be truthful to her because if she went nuts on me, I wanted a record with everyone that this chick beat me, cheated on me, and told me her dad died when he was alive and well.\n\nI left her and of course she went crazy, but I just kept ignoring her and this was pre social media, so it was easier to disappear.\n\nWatch for the crazy signs, she was ultra hot, but they get on that ultra hot scale and end up being fking crazy.    1
Name: text, dtype: int64


suspected_dict['Jreal22'] = 'Created at:2019-06-23, used the word f*ck in 28 negative comments in APR 17,18 2021'


# Check for this user account datah
df_users.query(" user_name == 'Jreal22' ")


df_jeral_contributions = df_jeral.groupby(df_jeral.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_jeral_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Jreal22" contributions in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 

fig.show()


df.text.value_counts().head()

[deleted]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            339
Amber Heard                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          268
### [Browse JerkOffChallenges](https://jerkofftocelebs.com/actors/)  • [Browse Picture Galleries](https://jerkofftocelebs.com/pictures/)  • NEW [JerkOffToGermanCelebs](https://reddit.com/r/JerkOffToGermanCelebs/)\n\n\n^(*Thank you for your submission. Make sure to follow the rules.*) \n\n^(*Check out our Website*) ^[*here*](https://jerkofftocelebs.com/). \n\n^(*Join our Discord*) ^[*here*](https://discord.gg/FMhrH2j).\n\n^(*Explore more subreddits*) ^[*here*](https://jerkofftocelebs.com/reddit-nsfw-list/).\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.*    161
[removed]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            122
Rule 9 overused. No Johny Depp or Amber Heard memes at this time\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/memes) if you have any questions or concerns.*                                                                                                                                                                                                                                                                                                                                                                                                                                                                                52
Name: text, dtype: int64


text = "can somebody rp as amber heard for me longterm"

df_rp = df[df.text.str.lower().str.contains(text)]

print(df_rp.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_rp.head())

(8, 17)


df_rp.subreddit.value_counts()

r/celebJObuds            5
r/CelebRoleplayJOBuds    2
r/CelebRoleplay          1
Name: subreddit, dtype: int64


df_rp.author.value_counts()

RoleplayTime21    3
RoleplayGuy21     3
-banned-          2
Name: author, dtype: int64


df_users.query("user_name in ['RoleplayGuy21', 'RoleplayTime21']")


text = "amber heard bad"

df_bad = df[df.text.str.lower().str.contains(text)]

print(df_bad.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_bad.head())

(36, 17)


df_bad.author.value_counts()

-banned-                14
bradje61                 3
ReShout876               2
SamGamer012              2
oldmanjenkins51          1
buwud                    1
Affectionate-Ad-2630     1
dansonquack              1
Raven_Force              1
Memelord96024            1
DuplicateDestroyer       1
HardcoreTristesse        1
KthulhuX                 1
Most-Programmer-1046     1
Sadclocktowernoises      1
LupLush                  1
YourMotherSaysHello      1
Lolthisistrash1234       1
skyrise011               1
Name: author, dtype: int64


bad_list = df_bad.author.value_counts().index.to_list()
bad_list = bad_list[1:]


df_users[df_users['user_name'].isin(bad_list)]


df_bad_contributions = df_bad.groupby(df_bad.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_bad_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Amber Heard Bad" contributions in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


text = "fuck amber heard"

df_fuc2 = df[df.text.str.lower().str.contains(text)]

print(df_fuc2.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_fuc2.head())

(102, 17)


df_fuc2.author.value_counts()

-banned-             13
FutureCrusaderX       2
RangaBro              1
throwaway340315       1
NotCayde6             1
                     ..
superzepto            1
fr0ntsight            1
Buckweed_420          1
ReallyBuffHamster     1
TitanGuppie           1
Name: author, Length: 89, dtype: int64


df_fuc2.subreddit.value_counts();


df_fuc2_submissions = df_fuc2.query(" submission_comment == 'submission' ")
print(df_fuc2_submissions.shape)
df_fuc2_submissions.head()

(31, 17)


df_fuc2_submissions.author.value_counts()

-banned-                12
adolfsdad                1
alexander_2084           1
ryzn02                   1
TitanGuppie              1
isaac0304                1
linglingthemetronome     1
itislwiaytime            1
dingusbob69              1
big_pog_human2478        1
OrientalDude             1
EmbodimentOfUwU          1
FrontpageWatch2020       1
LimpingIceberg           1
PlatinumDisc             1
guyinAmerica1            1
Sh0uldBeDoingSchool      1
throwaway340315          1
bigsquibb                1
Flerp6969                1
Name: author, dtype: int64


text = "good bot"

df_good = df[df.text.str.lower().str.contains(text)]

print(df_good.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_good.head())

(12, 17)


text = " bot "

df_bot = df[df.text.str.lower().str.contains(text)]

print(df_bot.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_bot.head())

(33, 17)


df_good.created_at.dt.date.value_counts()

2021-02-28    4
2021-03-04    3
2021-02-10    2
2021-01-09    1
2021-02-02    1
2021-05-01    1
Name: created_at, dtype: int64


df_good.subreddit.value_counts()

r/pussypassdenied    4
r/MensRights         3
r/TrueOffMyChest     3
r/EntitledBitch      1
r/awfuleverything    1
Name: subreddit, dtype: int64


df_good.author.value_counts()

loucos3               1
Iamabot3000           1
RunningBread888_yt    1
Amazing-Row-5963      1
chixnwafflez          1
HopelessMelancholy    1
Icr711                1
CaptainJackNarrow     1
jovinyo               1
CatchSufficient       1
apolocheese           1
aeon314159            1
Name: author, dtype: int64


text = "Amber Heard Touching Herself"

df_her = df[df.text.str.contains(text)]
# df_her = df_her.sort_values('created_at')

print(df_her.shape)
df_her.head()

(40, 17)


with pd.option_context('display.max_colwidth', None):
  display(df_her.head())


# drop the last column of the banned account to check bots behaviour on the same date 
df_bot = df_her.iloc[:-1, :]


df_bot.author.value_counts()

owenlinx             20
90police             17
garretdanielkelly     2
Name: author, dtype: int64


df_bot.submission_comment.value_counts()

submission    39
Name: submission_comment, dtype: int64


df_bot_contributions = df_bot.groupby(df_bot.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_bot_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Amber Heard Touching Herself" contributions in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_bot_contributions = df_bot.groupby(df_bot.created_at.dt.time).size().reset_index(name='n_contributions')

fig = px.bar(df_bot_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Amber Heard Touching Herself" contributions in 2021')

fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


# check these users other activities
df_bots = df[df['author'].isin(['owenlinx', '90police', 'garretdanielkelly'])]
print(df_bots.shape)
df_bots.head()

(39, 17)


# check their user data
df_users.query(" user_name in ['owenlinx', '90police', 'garretdanielkelly']")


text = "Amber Heard in Aquaman 2, why?"

df_aqua = df[df.text.str.contains(text)]
df_aqua = df_aqua.sort_values('created_at')

print(df_aqua.shape)
df_aqua.head() 

# .style.applymap(lambda x: helpers.coloring(x, {'Positive': '#deebce', 'Negative': '#edbcbb'}),
# subset=['sentiment_blob', 'sentiment_nltk'])

(13, 17)


with pd.option_context('display.max_colwidth', None):
  display(df_aqua.head())


df_aqua.author.value_counts()

Lecrapface    13
Name: author, dtype: int64


df_aqua.subreddit.value_counts()

r/PeopleBeingJerks        1
r/SupportForTheAccused    1
r/uwaterloo               1
r/MensRights              1
r/boxoffice               1
r/PussyPass               1
r/DC_Cinematic            1
r/entertainment           1
r/pussypassdenied         1
r/DC_Movies               1
r/JusticeForJohnnyDepp    1
r/CosmicBookNews          1
r/DeFranco                1
Name: subreddit, dtype: int64


df_aqua.top_level.value_counts()

submission    13
Name: top_level, dtype: int64


df_aqua.submission_comment.value_counts()

comment    13
Name: submission_comment, dtype: int64


# check the time frame in which these comments where written
df_aqua.created_at.dt.date.values[-1] - df_aqua.created_at.dt.date.values[0]

datetime.timedelta(0)


# check the time frame in which these comments where written
df_aqua.created_at.dt.hour.values[-1] - df_aqua.created_at.dt.hour.values[0]

1


# Check for this user account datah
df_users.query(" user_name == 'Lecrapface' ")


df_aqua_contributions = df_aqua.groupby(df_aqua.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_aqua_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Amber Heard in Aquaman 2, why?" contributions by Lecrapface in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_aqua_contributions = df_aqua.groupby(df_aqua.created_at.dt.hour).size().reset_index(name='n_contributions')


fig = px.bar(df_aqua_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Amber Heard in Aquaman 2, why?" contributions by Lecrapface in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


df_aqua_contributions = df_aqua.groupby(df_aqua.created_at.dt.strftime("%H:%M:%S")).size().reset_index(name='n_contributions')


fig = px.bar(df_aqua_contributions,
             x='created_at', 
             y='n_contributions', title='The number of "Amber Heard in Aquaman 2, why?" contributions by Lecrapface in 2021')
fig.update_traces(marker_color='red', marker_line_width=2, opacity=1, textposition='auto') 
# , marker_line_color='#5296dd'

fig.show()


suspected_dict['Lecrapface'] = "Created at: 2020-10-25 posted 'Amber Heard in Aquaman 2, why?' on 13 different subreddits in Jan 30, 2021"


print(f'Suspeted Dictionary: {suspected_dict}')

Suspeted Dictionary: {'Jreal22': 'Created at:2019-06-23, used the word f*ck in 28 negative comments in APR 17,18 2021', 'Lecrapface': "Created at: 2020-10-25 posted 'Amber Heard in Aquaman 2, why?' on 13 different subreddits in Jan 30, 2021"}


df_lecrapface = df.query(" author == 'Lecrapface'")
df_lecrapface = df_lecrapface.sort_values('created_at')

print(df_lecrapface.shape)
df_lecrapface.head(2)

(13, 17)


df['text_words'].value_counts().head(10);


px.histogram(df['text_words'].to_frame(), x="text_words",title='number of words in each contribution',
            nbins=200).update_traces(marker_color='#5296dd')


px.bar(data_frame=df['top_level'].value_counts().to_frame().reset_index(),
       x="index", y="top_level").update_layout(title='Comment or Submission (Top Level of Contrbution "Parent")',
                   xaxis_title='contribution top level (parent) category',
                   yaxis_title='number of contributions').update_traces(marker_color='#5296dd')


df['submission_text'].value_counts().head(10)

johnny_depp_releases_lapd_bodycam_footage_proving    1169
amber_heard                                          1068
amber_heard_has_been_fired_from_jason_momoas          933
emilia_clarke_to_replace_amber_heard_as_mera_in       739
DC_Cinematic                                          707
its_disgusting_that_people_are_less_angry_about       686
amber_heard_is_a_monster_a_gold_digger_looking        609
amber_heard_still_in_aquaman_2_despite_proof_that     481
fuck_amber_heard                                      376
does_the_amber_heard_story_prove_that_men_will        358
Name: submission_text, dtype: int64


df_mera = df.query(" submission_text == 'emilia_clarke_to_replace_amber_heard_as_mera_in' & \
                           submission_comment == 'submission' ")
print(df_mera.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_mera.head())

(6, 17)


li = list(df_mera.author.unique())
li.remove('-banned-')
df_users[df_users.user_name.isin(li)]


df_mera_comments = df.query(" submission_text == 'emilia_clarke_to_replace_amber_heard_as_mera_in' ")
print(df_mera_comments.shape)
df_mera_comments.head(1)

(739, 17)


df_mera_contributions = df_mera_comments.groupby(df_mera_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_contributions.head(7),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_mera_contributions.head(7).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_mera_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_mera_authors = df_mera_comments.groupby(df_mera_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_mera_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_mera_comments[df_mera_comments.author == 'someonesgranpa'];


df_momos = df.query(" submission_text == 'amber_heard_has_been_fired_from_jason_momoas' & \
                           submission_comment == 'submission' ")
print(df_momos.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_momos.head())

(4, 17)


li = list(df_momos.author.unique())
df_users[df_users.user_name.isin(li)]


df_momos_comments = df.query(" submission_text == 'amber_heard_has_been_fired_from_jason_momoas' ")
print(df_momos_comments.shape)
df_momos_comments.head(1)

(933, 17)


df_momos_contributions = df_momos_comments.groupby(df_momos_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_momos_contributions.head(4),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_momos_contributions.head(4).created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_momos_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_momos_authors = df_momos_comments.groupby(df_momos_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_momos_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df_momos_comments[df_momos_comments.author == 'JenkinMan'];
# All negative comments


df_momos_comments[df_momos_comments.author == 'JenkinMan']
df_users.query(" user_name in ['JenkinMan']")


df_lapd = df.query(" submission_text == 'johnny_depp_releases_lapd_bodycam_footage_proving' & \
                           submission_comment == 'submission' ")
print(df_lapd.shape)

with pd.option_context('display.max_colwidth', None):
  display(df_lapd.head(1))

(3, 17)


df_users.query(" user_name in ['Gato1980', 'autotldr', 'Danger3214']")


df_lapd_comments = df.query(" submission_text == 'johnny_depp_releases_lapd_bodycam_footage_proving' ")
print(df_lapd_comments.shape)
df_lapd_comments.head()

(1169, 17)


df_lapd_contributions = df_lapd_comments.groupby(df_lapd_comments.created_at.dt.date).size().reset_index(name='n_contributions')


fig = px.bar(df_lapd_contributions.head(),
             x='created_at', 
             y='n_contributions', title='The number of contributions/date on these submissions')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_lapd_contributions.head().created_at,
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_lapd_contributions.n_contributions] 

fig.update_traces(marker_color=clrs, marker_line_width=1.5, opacity=1, textposition='auto')

fig.show()


df_lapd_authors = df_lapd_comments.groupby(df_lapd_comments.author).size().reset_index(name='n_contributions')


fig = px.bar(df_lapd_authors,
             x='author', 
             y='n_contributions', title='The number of contributions per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,25])

fig.show()


df.parent_id.value_counts().head()

t3_lu5055    318
t3_lo748q    233
t3_n9lwnf    193
t3_lx2s7w    186
t3_kyj460    167
Name: parent_id, dtype: int64


fig = px.bar(df.parent_id.value_counts().to_frame().head(25).reset_index(), x="parent_id", y="index",
             height=500,
             title='sumbissions with most comments (Top Level Comments)').update_layout(
                   xaxis_title='Number of comments',
                   yaxis_title='subbredit').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


df_top5 = df_merged[df_merged.child_id.isin(df_merged.parent_id.value_counts().head().index)]

with pd.option_context('display.max_colwidth', None):
  display(df_top5)


df_merged.submission_text = df_merged.submission_text.str.replace('_', ' ')


# get a list with the top 5 submission text
top5_text = list(df_top5.text)


def compare(str):
    for text in top5_text:
        if str in text:
            return True
        else: return False


mask = df_merged.submission_text.apply(compare)

df_top5_contributions1 = df_merged[mask]

df_top5_authors = df_top5_contributions1.groupby(df_top5_contributions1.user_name).size().reset_index(name='n_contributions')

fig = px.bar(df_top5_authors,
             x='user_name', 
             y='n_contributions', title='The number comments per author on these submissions')

fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 

fig.show()


df_top5_contributions1.shape

(45, 24)


df_top5_contributions2 = df_merged[df_merged.parent_id.isin(df_merged.parent_id.value_counts().head().index)]

df_top5_authors = df_top5_contributions2.groupby(df_top5_contributions2.user_name).size().reset_index(name='n_contributions')


fig = px.bar(df_top5_authors,
             x='user_name', 
             y='n_contributions', title='The number of parent comments per author on these submissions')
fig.update_traces(marker_color='#5296dd', opacity=1, textposition='auto') 
# , marker_line_color='#5296dd', marker_line_width=2

fig.update_yaxes(range = [0,5])

fig.show()


df_top5_contributions2.shape

(1097, 24)


df_submissions = df[df.submission_comment == 'submission']
print(df_submissions.shape)
df_submissions.head(2)

(1925, 17)


df_submissions.author.value_counts().nlargest(n=10)

-banned-               535
charliedba              98
LoveAmberHeard42286     97
Truthbetheprejudice     43
CelebBattleVoteBot      42
YahYah241               26
owenlinx                20
the-speed-of-pain       20
shalanarose             20
90police                17
Name: author, dtype: int64


df_submissions.author.value_counts().to_frame().head(10)


fig = px.bar(df_submissions.author.value_counts().to_frame().head(10).reset_index(), x="author", y="index",
             height=500,
             title='Authors with most Submissions').update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='Number of Negative Submissions',
                   yaxis_title='Author_Name').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


df_submissions.author.value_counts().head()

-banned-               535
charliedba              98
LoveAmberHeard42286     97
Truthbetheprejudice     43
CelebBattleVoteBot      42
Name: author, dtype: int64


check_list = df_submissions.author.value_counts().nlargest(n=25).index.tolist()[1:]
check_list

['charliedba',
 'LoveAmberHeard42286',
 'Truthbetheprejudice',
 'CelebBattleVoteBot',
 'YahYah241',
 'owenlinx',
 'the-speed-of-pain',
 'shalanarose',
 '90police',
 'celebnationofficial',
 'Sleeper1034',
 'newsfeedmedia',
 'Just_Perception_7965',
 'cptn3sm10',
 'SableFilms',
 'templederr',
 'chicago_bastard',
 'Bill8379',
 'AdricDrake',
 'Korrocks',
 'MikiSayaka33',
 'Stark8945',
 'VAYU3594',
 'krttz35']


# get a data frame with the most negative-comments users
df_check = df_users[df_users['user_name'].isin(check_list)]
print(df_check.shape)
df_check.head(2)

(24, 10)


df_check['user_name'].nunique()

24


for col in df_check.columns:
    if col not in ['user_name', 'user_created_at']:
        print('The value counts of the users with the most submissions: ' + col)
        print(df_check[col].value_counts())
        print('\n')

The value counts of the users with the most submissions: has_verified_email
True     23
False     1
Name: has_verified_email, dtype: int64


The value counts of the users with the most submissions: is_mod
True     16
False     8
Name: is_mod, dtype: int64


The value counts of the users with the most submissions: is_gold
False    19
True      5
Name: is_gold, dtype: int64


The value counts of the users with the most submissions: is_banned
False    20
True      4
Name: is_banned, dtype: int64


The value counts of the users with the most submissions: comment_karma
0.0        2
754.0      2
101.0      1
11983.0    1
2.0        1
27550.0    1
124.0      1
405.0      1
285.0      1
5.0        1
146.0      1
1436.0     1
40.0       1
95386.0    1
52.0       1
25.0       1
1063.0     1
1.0        1
Name: comment_karma, dtype: int64


The value counts of the users with the most submissions: link_karma
3388.0     1
20315.0    1
11539.0    1
74998.0    1
8374.0     1
25263.0    1
1641.0     1
2698.0     1
49114.0    1
749.0      1
865.0      1
32197.0    1
5153.0     1
2012.0     1
175.0      1
19887.0    1
16991.0    1
14007.0    1
1653.0     1
1.0        1
Name: link_karma, dtype: int64


The value counts of the users with the most submissions: banned_unverified
others        19
banned         4
unverified     1
Name: banned_unverified, dtype: int64


The value counts of the users with the most submissions: creation_year
2020      7
2021      6
banned    4
2019      4
others    2
2018      1
Name: creation_year, dtype: int64


df['urls'].nunique()

233


df[df.astype(str)['urls'] != '[]'].head(2)


df['urls'].astype('str').value_counts().head()

[]                                                                                                                                                                          17522
['https://jerkofftocelebs.com', 'https://jerkofftocelebs.com', 'https://reddit.com', 'https://jerkofftocelebs.com', 'https://discord.gg', 'https://jerkofftocelebs.com']      161
['https://www.reddit.com']                                                                                                                                                     49
['https://reddit.com']                                                                                                                                                         43
['https://redd.it', 'https://www.instagram.com']                                                                                                                               42
Name: urls, dtype: int64


# the value counts of the # of urls
df['urls_count'].value_counts();


fig = px.histogram(df['urls_count'].to_frame(), x="urls_count",title='Count of the number of URLS in each Contribution',
            nbins=130).update_traces(marker_color='#5296dd')

fig.update_layout(
    xaxis = dict(
        tickmode = 'array',
        tickvals = df['urls_count'],
    )
)

fig.show()


px.histogram(df[~(df['urls_count'].isin([0,60,20,16]))], x="urls_count",title='Count of the number of URLS in each Contribution',
            nbins=20).update_traces(marker_color='#5296dd')


fig = px.histogram(df['submission_words'].to_frame(), x="submission_words",
                   title='number of words in submission text',
                   nbins=50).update_traces(marker_color='#5296dd')

fig.update_layout(
    xaxis = dict(
        title='Number of submission words',
        tickmode = 'linear',
    )
)


df['subreddit'].nunique()

545


df['subreddit'] = df['subreddit'].str[:]


df.subreddit.value_counts().to_frame().head(20).reset_index()


fig = px.bar(df.subreddit.value_counts().to_frame().head(20).reset_index(), x="subreddit", y="index",
             height=500,
             title='Most used subbredits').update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='Number of comments',
                   yaxis_title='subbredit').update_traces(marker_color='#5296dd')

fig.update_yaxes(autorange="reversed")


# note that value_counts() neglect Zeros
df_merged["days_after_creation"].value_counts()

3449.0    60
3343.0    59
3393.0    57
3405.0    55
3394.0    54
          ..
2904.0     1
3993.0     1
1790.0     1
1789.0     1
2150.0     1
Name: days_after_creation, Length: 3290, dtype: int64


px.histogram(df_merged, x="days_after_creation",title='days_after_creation',
            nbins=250).update_traces(marker_color='#5296dd',).update_layout(
                   xaxis_title='number of days',)


print('The number of accounts posted the same day they was created!')
df_merged[df_merged['days_after_creation'] == 0].shape[0]

The number of accounts posted the same day they was created!

45


print('The number of accounts posted the same week they was created!')
df_merged[df_merged['days_after_creation'] <= 7].shape[0]

The number of accounts posted the same week they was created!

150


print('The number of accounts posted the same month they was created!')
df_merged[df_merged['days_after_creation'] <= 30].shape[0]

The number of accounts posted the same month they was created!

451


df_merged[df_merged['days_after_creation'] <= 30]['user_created_at'].dt.year.value_counts()

2021    385
2020     66
Name: user_created_at, dtype: int64


mask = (df_merged['days_after_creation'] <= 30) & (df_merged['user_created_at'].dt.year == 2021)
df_merged[mask]['user_created_at'].dt.strftime('%b').value_counts()

Jan    105
Feb     82
Apr     82
Mar     80
May     36
Name: user_created_at, dtype: int64


months = df_merged[df_merged['days_after_creation'] <= 30]['user_created_at'].dt.strftime('%b')
months_sorted = months.value_counts()[['Jan', 'Feb', 'Mar', 'Apr', 'May']]
months_sorted

Jan    105
Feb     82
Mar     80
Apr     82
May     36
Name: user_created_at, dtype: int64


fig = px.bar(months_sorted,
             x=months_sorted.index, y=months_sorted.values, text=months_sorted.values)

fig.update_layout(
            title={
        'text': "contributions of the accounts posted/commented <br> the same month they were created",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

# fig.update_layout(
#     xaxis = dict(
#         title='Month(2021)',
#         tickmode = 'array',
#         tickvals = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
#         ticktext = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
#         )
# )

clrs = ['red' if (y > 100) else '#5296dd' for y in months_sorted.values] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


# months_sorted.plot(kind='bar', figsize=(8,8), title='contributions of the accounts posted/commented \n the same month they were created');


# THE SAME MONTH:
# check for the date these accounts posted/commented 
reddit_30 = df_merged[df_merged['days_after_creation'] <= 30]

dates_count = df_merged.groupby(reddit_30['created_at'].dt.date).size().reset_index(name='contributions')
dates_count.sort_values('contributions', ascending=False);


fig = px.bar(dates_count,
             x='created_at', 
             y='contributions', title = 'contributions of the accounts posted/commented the same month they were created')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# THE SAME WEEK
# check for the date these accounts posted/commented
reddit_7 = df_merged[df_merged['days_after_creation'] <= 7]

dates_count_7 = df_merged.groupby(reddit_7['created_at'].dt.date).size().reset_index(name='contributions')
dates_count_7.sort_values('contributions', ascending=False);


fig = px.bar(dates_count_7,
             x='created_at', 
             y='contributions', title = 'contributions of the accounts posted/commented the same week they were created')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# THE SAME DAY
# check for the date these accounts posted/commented
reddit_1 = df_merged[df_merged['days_after_creation'] <= 0]

dates_count_1 = df_merged.groupby(reddit_1['created_at'].dt.date).size().reset_index(name='contributions')
dates_count_1.sort_values('contributions', ascending=False);


fig = px.bar(dates_count_1,
             x='created_at', 
             y='contributions', title = 'contributions of the accounts posted/commented the same day they were created')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# get the author names that commented in a negative way the same month the account was created
# to add to the suspected list
df_merged_30 = df_merged.query("days_after_creation <= 30 & sentiment_blob == sentiment_nltk == 'Negative' ")
df_merged_30.head()


# suspected5 = (df_merged_30.user_name).tolist()

# set(suspected5) & set(suspected_list)


# suspected_list = suspected_list + suspected5


# with pd.option_context('display.max_colwidth', None):
#   display(df_merged.query("user_name == 'LoveAmberHeard42286' ").text.head())


# suspected_list.remove('LoveAmberHeard42286')


# len(suspected_list)


# group by creation year and count 
df_contributions = df_merged.groupby(df_merged['user_created_at'].dt.year).size().reset_index(name='n_accounts')

fig = px.bar(df_contributions,
             x='user_created_at', y='n_accounts', text='n_accounts', title='Number of User Accounts Created in each year / having contributions in 2021')
fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


# base_color = sb.color_palette()[0]
# clrs = ['red' if (y > 4000) else base_color for y in df.groupby(df.created_at.dt.month).size()] 

# fig, ax = plt.subplots()
# fig.set_size_inches(11.7, 8.27)
# sb.countplot(x = df['created_at'].dt.month, data = df, palette=clrs)
# plt.xlabel('Months', fontsize=14)
# plt.ylabel('Contributions Count', fontsize=14)
# plt.title('Contributions count over Months in 2021', fontsize=18)
# plt.show()


fig = px.bar(df.groupby(df['created_at'].dt.month).size().reset_index(name='contribution_count'),
             x='created_at', y='contribution_count', text='contribution_count')

fig.update_layout(
            title={
        'text': "Estimation of the number contributions created in each month of 2021",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='Month(2021)',
        tickmode = 'array',
        tickvals = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
        ticktext = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
        )
)

clrs = ['red' if (y > 4000) else '#5296dd' for y in df.groupby(df['created_at'].dt.month).size()] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


# base_color = sb.color_palette()[0]
# clrs = ['red' if (y > 1500) else base_color for y in df.groupby(df.created_at.dt.day).size()] 

# fig, ax = plt.subplots()
# fig.set_size_inches(11.7, 8.27)
# sb.countplot(x = df['created_at'].dt.day, data = df, palette=clrs)
# plt.xlabel('Months', fontsize=14)
# plt.ylabel('Contributions Count', fontsize=14)
# plt.title('Contributions count over Days of month in 2021', fontsize=18)
# plt.show()


fig = px.bar(df.groupby(df['created_at'].dt.day).size().reset_index(name='contribution_count'),
             x='created_at', y='contribution_count', text='contribution_count')

fig.update_layout(
            title={
        'text': "Estimation of the number contributions created in each DayOfMonth in 2021",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='Month Days(2021)',
        tickmode = 'linear',
    )
)



clrs = ['red' if (y > 1500) else '#5296dd' for y in df.groupby(df['created_at'].dt.day).size()] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


week_day = df['created_at'].dt.strftime('%a')
# one can sort by any order by providing a custom index explicitely :
# https://stackoverflow.com/questions/43855474/changing-sort-in-value-counts/43855492
week_sorted = week_day.value_counts()[['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']]
week_sorted

Mon    2172
Tue    2640
Wed    1824
Thu    2160
Fri    1779
Sat    4763
Sun    2967
Name: created_at, dtype: int64


fig = px.bar(df.groupby(df['created_at'].dt.dayofweek).size().reset_index(name='contribution_count'),
             x='created_at', y='contribution_count', text='contribution_count')

fig.update_layout(
            title={
        'text': "Estimation of the number contributions created in each DayOfWeek (2021)",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='DayOfWeek(2021)',
        tickmode = 'array',
        tickvals = [0, 1, 2, 3, 4, 5, 6],
        ticktext = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
        )
)

clrs = ['red' if (y > 4000) else '#5296dd' for y in df.groupby(df['created_at'].dt.dayofweek).size()] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto')
fig.show()


# check for the hour the contributions were made
df_hours = df.groupby(df['created_at'].dt.hour).size().reset_index(name='contribution_count')
# df_hours.sort_values('contribution_count', ascending=False);   


fig = px.bar(df_hours,
             x='created_at', y='contribution_count', 
             title='Number of contrbutions Comment/Submission in day hours (2021)')

fig.update_layout(
    xaxis = dict(
        title='Hours of Day',
        tickmode = 'linear',
        dtick = 1
    )
)

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


df.created_at.dt.date.value_counts().head()

2021-04-17    1341
2021-02-20     931
2021-02-28     855
2021-05-11     612
2021-03-04     606
Name: created_at, dtype: int64


# # group by date an count
# trendy_dates = df.groupby(df['created_at'].dt.date).agg('count')['created_at'].to_frame()

# # naming the count column as  contribution_count
# trendy_dates.columns = ['contribution_count']
# trendy_dates.sort_values('contribution_count', ascending=False, inplace=True)

# trendy_dates = trendy_dates.reset_index()


trendy_dates = df.groupby(df['created_at'].dt.date).size().reset_index(name='contribution_count')

fig = px.bar(trendy_dates,
             x='created_at', y='contribution_count')

fig.update_layout(
            title={
        'text': "The number of contributions created in each date",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


trendy_dates.sort_values('contribution_count', ascending=False)


# get the top 5 trendy dates first, then sort them by date
top_trendy_dates = trendy_dates.head(5)
top_trendy_dates.sort_values('created_at', inplace=True)


top_trendy_dates


top_trendy_dates.reset_index(inplace=True)


fig = px.bar(top_trendy_dates,
             x='created_at', y='contribution_count', title='Number of contrbutions Comment/Submission in trendy dates')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = top_trendy_dates.created_at,
    )
)

clrs = ['red' if (y > 400) else '#5296dd' for y in top_trendy_dates.contribution_count] 

fig.update_traces(marker_color=clrs,
                  opacity=1, textposition='auto').update_layout()

# marker_line_width=1.5,

fig.show()


# check for the number of accounts contributed on the peak day (Apr 17,2021)
df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-04-17'].user_name.nunique()

699


df_merged_peak1 = df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-04-17']


# check for the year the accounts were created
df_user_year1 = df_merged_peak1.groupby(df_merged_peak1['user_created_at'].dt.year).size().reset_index(name='contribution_count')

fig = px.bar(df_user_year1,
             x='user_created_at', y='contribution_count', 
             title='The creation year of the accounts contributed on the peak day (Apr 17,2021)')

fig.update_layout(
    xaxis = dict(
        title='Accout Creation Year',
        tickmode = 'linear',
        dtick = 1
    )
)

clrs = ['red' if (y > 250) else '#5296dd' for y in df_user_year1.contribution_count] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


df_peak_1 = df[df.created_at.dt.strftime('%Y-%m-%d') == '2021-04-17']

# check for the hour the contributions were made
df_hours = df_peak_1.groupby(df['created_at'].dt.hour).size().reset_index(name='contribution_count')
# df_hours.sort_values('contribution_count', ascending=False);   


fig = px.bar(df_hours,
             x='created_at', y='contribution_count', 
             title='Number of contrbutions Comment/Submission in day hours')

fig.update_layout(
    xaxis = dict(
        title='Hours of Day',
        tickmode = 'linear',
        dtick = 1
    )
)

clrs = ['red' if (y > 80) else '#5296dd' for y in df_hours.contribution_count] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# check for the number of accounts contributed on the peak day (Feb 20,2021)
df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-02-20'].user_name.nunique()

626


df_merged_peak2 = df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-02-20']


# check for the year the accounts were created
df_user_year2 = df_merged_peak2.groupby(df_merged_peak2['user_created_at'].dt.year).size().reset_index(name='contribution_count')

fig = px.bar(df_user_year2,
             x='user_created_at', y='contribution_count', 
             title='The creation year of the accounts contributed on the peak day (Feb 20,2021)')

fig.update_layout(
    xaxis = dict(
        title='Accout Creation Year',
        tickmode = 'linear',
        dtick = 1
    )
)

clrs = ['red' if (y > 100) else '#5296dd' for y in df_user_year2.contribution_count] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


df_peak_2 = df[df.created_at.dt.strftime('%Y-%m-%d') == '2021-02-20']


# check for the hour the contributions were made
df_hours = df_peak_2.groupby(df['created_at'].dt.hour).size().reset_index(name='contribution_count')
# df_hours.sort_values('contribution_count', ascending=False);   


fig = px.bar(df_hours,
             x='created_at', y='contribution_count', 
             title='Number of contrbutions Comment/Submission in day hours')

fig.update_layout(
    xaxis = dict(
        title='Hours of Day',
        tickmode = 'linear',
        dtick = 1
    )
)

clrs = ['red' if (y > 200) else '#5296dd' for y in df_hours['contribution_count']] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# check for the number of accounts contributed on the peak day (Feb 28,2021)
df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-02-28'].user_name.nunique()

617


df_merged_peak3 = df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-02-28']


# check for the year the accounts were created
df_user_year3 = df_merged_peak3.groupby(df_merged_peak3['user_created_at'].dt.year).size().reset_index(name='contribution_count')

fig = px.bar(df_user_year3,
             x='user_created_at', y='contribution_count', 
             title='The creation year of the accounts contributed on the peak day (Feb 28,2021)')

fig.update_layout(
    xaxis = dict(
        title='Accout Creation Year',
        tickmode = 'linear',
        dtick = 1
    )
)

clrs = ['red' if (y > 140) else '#5296dd' for y in df_user_year3['contribution_count']] 


fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# # check for the accounts contributed on the peak day (Feb 28,2021)
# df_merged[df_merged.created_at.dt.strftime('%Y-%m-%d') == '2021-02-28']\
# .user_created_at.dt.year.value_counts().sort_index().plot(kind='bar', figsize=(13,8));

# # plt.gca().invert_xaxis()
# plt.title('The creation year of the accounts contributed on the peak day (Feb 28,2021)', fontsize=18);
# plt.xlabel('Accout Creation Year', fontsize=14);
# plt.ylabel('n_contributions', fontsize=14);


df_peak_3 = df[df.created_at.dt.strftime('%Y-%m-%d') == '2021-02-28']

# check for the hour the contributions were made
df_hours = df.groupby(df['created_at'].dt.hour).size().reset_index(name='contribution_count')
# df_hours.sort_values('contribution_count', ascending=False);   


fig = px.bar(df_hours,
             x='created_at', y='contribution_count', 
             title='Number of contrbutions Comment/Submission in day hours')

fig.update_layout(
    xaxis = dict(
        title='Hours of Day',
        tickmode = 'linear',
        dtick = 1
    )
)

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


# df_merged.hist(figsize=(21,21), color='#5296dd', xrot = 90);
# # plt.xticks(rotation=90);

	created_at	n_contributions
0	2021-04-18	3
1	2021-04-20	4
2	2021-04-29	4
3	2021-04-30	4
4	2021-05-07	8
5	2021-05-08	5
6	2021-05-09	5
7	2021-05-10	5
8	2021-05-19	5

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
8257	t3_lqz7bz	/r/celebJObuds/comments/lqz7bz/can_somebody_rp_as_amber_heard_for_me_longterm/	Can Somebody RP as Amber Heard for me longterm?	NaN	r/celebJObuds	-banned-	2021-02-24 01:12:29	Neutral	Neutral	2.0	NaN	submission	9	can_somebody_rp_as_amber_heard_for_me_longterm	9	[]
8341	t3_lrt0zh	/r/celebJObuds/comments/lrt0zh/can_somebody_rp_as_amber_heard_for_me_longterm/	Can Somebody RP as Amber Heard for me longterm?	NaN	r/celebJObuds	RoleplayGuy21	2021-02-25 01:11:34	Neutral	Neutral	6.0	NaN	submission	9	can_somebody_rp_as_amber_heard_for_me_longterm	9	[]
8390	t3_lsfc05	/r/celebJObuds/comments/lsfc05/can_somebody_rp_as_amber_heard_for_me_longterm/	Can Somebody RP as Amber Heard for me longterm?	NaN	r/celebJObuds	RoleplayGuy21	2021-02-25 19:57:10	Neutral	Neutral	4.0	NaN	submission	9	can_somebody_rp_as_amber_heard_for_me_longterm	9	[]
8417	t3_lsgxdx	/r/celebJObuds/comments/lsgxdx/can_somebody_rp_as_amber_heard_for_me_longterm/	Can Somebody RP as Amber Heard for me longterm?	NaN	r/celebJObuds	RoleplayGuy21	2021-02-25 21:07:11	Neutral	Neutral	14.0	NaN	submission	9	can_somebody_rp_as_amber_heard_for_me_longterm	9	[]
8472	t3_lt8ipk	/r/celebJObuds/comments/lt8ipk/can_somebody_rp_as_amber_heard_for_me_longterm/	Can Somebody RP as Amber Heard for me longterm?	NaN	r/celebJObuds	-banned-	2021-02-26 21:38:12	Neutral	Neutral	2.0	NaN	submission	9	can_somebody_rp_as_amber_heard_for_me_longterm	9	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
6601	t3_lo748q	/r/entertainment/comments/lo748q/emilia_clarke_to_replace_amber_heard_as_mera_in/	Emilia Clarke to Replace Amber Heard As Mera In Aquaman 2? - FandomWire	NaN	r/entertainment	UltraMagnus0001	2021-02-20 13:27:20	Neutral	Neutral	17412.0	NaN	submission	13	emilia_clarke_to_replace_amber_heard_as_mera_in	9	[]
7459	t3_lon83n	/r/EmiliaClarke/comments/lon83n/emilia_clarke_to_replace_amber_heard_as_mera_in/	Emilia Clarke to Replace Amber Heard As Mera In Aquaman 2?	NaN	r/EmiliaClarke	-banned-	2021-02-21 02:47:15	Neutral	Neutral	1.0	NaN	submission	11	emilia_clarke_to_replace_amber_heard_as_mera_in	9	[]
7568	t3_lovxnz	/r/movies/comments/lovxnz/emilia_clarke_to_replace_amber_heard_as_mera_in/	Emilia Clarke to Replace Amber Heard As Mera In Aquaman 2? - FandomWire	NaN	r/movies	-banned-	2021-02-21 12:15:57	Neutral	Neutral	9.0	NaN	submission	13	emilia_clarke_to_replace_amber_heard_as_mera_in	9	[]
7579	t3_low6va	/r/movies/comments/low6va/emilia_clarke_to_replace_amber_heard_as_mera_in/	Emilia Clarke to Replace Amber Heard As Mera In Aquaman 2?	NaN	r/movies	Watcher2020	2021-02-21 12:32:33	Neutral	Neutral	21.0	NaN	submission	11	emilia_clarke_to_replace_amber_heard_as_mera_in	9	[]
7715	t3_lp6ttu	/r/MensRights/comments/lp6ttu/emilia_clarke_to_replace_amber_heard_as_mera_in/	Emilia Clarke to Replace Amber Heard As Mera In Aquaman 2?	NaN	r/MensRights	UnHope20	2021-02-21 21:15:31	Neutral	Neutral	132.0	NaN	submission	11	emilia_clarke_to_replace_amber_heard_as_mera_in	9	[]

	index	author
0	-banned-	1587
1	AutoModerator	515
2	CelebBattleVoteBot	163
3	LoveAmberHeard42286	124
4	charliedba	99
5	Stanley_Elkind	44
6	Truthbetheprejudice	43
7	gaul66	37
8	Beatplayer	32
9	sadwook	32

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls	urls_count
0	t3_ko1ew0	/r/CelebbattlePolls/comments/ko1ew0/marvel_vs_...	Marvel vs DC : Team Marvel (Evangeline Lilly B...	NaN	r/CelebbattlePolls	CelebBattleVoteBot	2021-01-01 00:23:29	Neutral	Positive	1.0	NaN	submission	25	marvel_vs_dc_team_marvel_evangeline_lilly_brie	8	[]	0
1	t1_ghnp3w4	/r/CelebbattlePolls/comments/ko1ew0/marvel_vs_...	Poll for [Marvel vs DC : Team Marvel (Evangeli...	t3_ko1ew0	r/CelebbattlePolls	CelebBattleVoteBot	2021-01-01 00:23:30	Neutral	Positive	1.0	submission	comment	29	marvel_vs_dc_team_marvel_evangeline_lilly_brie	8	['https://reddit.com']	1
2	t1_ghnp3wq	/r/CelebBattles/comments/ko1duk/marvel_vs_dc_t...	Vote here: https://www.reddit.com/poll/ko1ew0\...	t3_ko1duk	r/CelebBattles	CelebBattleVoteBot	2021-01-01 00:23:30	Positive	Neutral	1.0	submission	comment	12	marvel_vs_dc_team_marvel_evangeline_lilly_brie	8	['https://www.reddit.com']	1
3	t3_kp2soe	/r/CelebbattlePolls/comments/kp2soe/rachel_mca...	Rachel McAdams vs Amber Heard	NaN	r/CelebbattlePolls	CelebBattleVoteBot	2021-01-02 18:35:07	Neutral	Neutral	2.0	NaN	submission	5	rachel_mcadams_vs_amber_heard	5	[]	0
4	t1_ghul208	/r/CelebbattlePolls/comments/kp2soe/rachel_mca...	Poll for [Rachel McAdams vs Amber Heard](https...	t3_kp2soe	r/CelebbattlePolls	CelebBattleVoteBot	2021-01-02 18:35:07	Neutral	Neutral	1.0	submission	comment	9	rachel_mcadams_vs_amber_heard	5	['https://reddit.com']	1

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t3_ms8xkq	/r/Amber_Heard/comments/ms8xkq/long_legged_bea...	Long legged beauty [Amber Heard]	NaN	r/Amber_Heard	charliedba	2021-04-16 18:07:26	Negative	Positive	1.0	NaN	submission	5	Amber_Heard	2	[]
1	t3_msbo0x	/r/BeautifulFemales/comments/msbo0x/amber_hear...	Amber Heard [irtr]	NaN	r/BeautifulFemales	charliedba	2021-04-16 20:23:46	Neutral	Neutral	29.0	NaN	submission	3	amber_heard_irtr	3	[]
2	t3_mtkdvb	/r/Amber_Heard/comments/mtkdvb/angelic_smile_a...	Angelic smile [Amber Heard]	NaN	r/Amber_Heard	charliedba	2021-04-18 20:08:57	Positive	Positive	1.0	NaN	submission	4	Amber_Heard	2	[]
3	t3_mtkfg1	/r/UHQcelebs/comments/mtkfg1/amber_heard_2100_...	Amber Heard [2100 x 3150]	NaN	r/UHQcelebs	charliedba	2021-04-18 20:11:13	Neutral	Neutral	55.0	NaN	submission	5	amber_heard_2100_x_3150	5	[]
4	t3_mtkgku	/r/FamousFaces/comments/mtkgku/amber_heard_210...	Amber Heard [2100 x 3150]	NaN	r/FamousFaces	charliedba	2021-04-18 20:12:54	Neutral	Neutral	5.0	NaN	submission	5	amber_heard_2100_x_3150	5	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t1_gmzc8ly	/r/JerkOffToCelebs/comments/lhu3nv/amber_heard...	I would put it in every one of her holes	t3_lhu3nv	r/JerkOffToCelebs	Stanley_Elkind	2021-02-11 20:42:48	Neutral	Neutral	3.0	submission	comment	10	amber_heard	2	[]
1	t1_gnf1pv3	/r/DC_Cinematic/comments/ljqbut/discussion_hon...	Everyone is cool burgeoning cult leader Jared ...	t3_ljqbut	r/DC_Cinematic	Stanley_Elkind	2021-02-14 15:28:05	Positive	Positive	1.0	submission	comment	9	DC_Cinematic	2	[]
2	t1_gni2nrr	/r/JerkOffToCelebs/comments/lk5bc8/cant_help_b...	Black widow	t3_lk5bc8	r/JerkOffToCelebs	Stanley_Elkind	2021-02-15 04:21:15	Negative	Neutral	1.0	submission	comment	2	cant_help_but_notice_the_way_she_looks_at_you_now	11	[]
3	t1_gnuualx	/r/JerkOffToCelebs/comments/lmc28b/amber_heard...	The more people hate her the more I want to fu...	t3_lmc28b	r/JerkOffToCelebs	Stanley_Elkind	2021-02-18 05:36:20	Negative	Neutral	3.0	submission	comment	12	amber_heard_could_do_with_a_skull_fucking	8	[]
4	t1_go1jx5r	/r/JerkOffToCelebs/comments/lnodlf/amber_heard...	I can’t be quit her. I don’t want to.	t3_lnodlf	r/JerkOffToCelebs	Stanley_Elkind	2021-02-19 20:01:40	Neutral	Positive	1.0	submission	comment	9	amber_heard_is_the_sexiest_psycho_i_ever_saw	9	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t3_mtioam	/r/MensRights/comments/mtioam/johnny_depp_seen...	Johnny Depp Seen In Rare Photos In Spain, As H...	NaN	r/MensRights	Truthbetheprejudice	2021-04-18 18:41:42	Positive	Neutral	1.0	NaN	submission	17	johnny_depp_seen_in_rare_photos_in_spain_as_his	10	[]
1	t3_mtjtsr	/r/movies/comments/mtjtsr/johnny_depp_makes_an...	Johnny Depp Makes an Appearance in Spain as La...	NaN	r/movies	Truthbetheprejudice	2021-04-18 19:40:25	Positive	Negative	1.0	NaN	submission	16	johnny_depp_makes_an_appearance_in_spain_as	8	[]
2	t3_mtkogv	/r/entertainment/comments/mtkogv/johnny_depp_m...	Johnny Depp Makes an Appearance in Spain as La...	NaN	r/entertainment	Truthbetheprejudice	2021-04-18 20:24:14	Positive	Negative	1.0	NaN	submission	16	johnny_depp_makes_an_appearance_in_spain_as	8	[]
3	t3_muyp3k	/r/MensRights/comments/muyp3k/justiceforjohnny...	#JusticeForJohnnyDepp Johnny Depp fans donate ...	NaN	r/MensRights	Truthbetheprejudice	2021-04-20 19:47:45	Neutral	Negative	75.0	NaN	submission	12	justiceforjohnnydepp_johnny_depp_fans_donate_40k	6	[]
4	t3_muypet	/r/entertainment/comments/muypet/justiceforjoh...	#JusticeForJohnnyDepp Johnny Depp fans donate ...	NaN	r/entertainment	Truthbetheprejudice	2021-04-20 19:48:06	Neutral	Negative	1.0	NaN	submission	12	justiceforjohnnydepp_johnny_depp_fans_donate_40k	6	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t1_ghobzuy	/r/CelebBattles/comments/ko1duk/marvel_vs_dc_t...	Marvel	t3_ko1duk	r/CelebBattles	gaul66	2021-01-01 04:29:09	Neutral	Positive	8.0	submission	comment	1	marvel_vs_dc_team_marvel_evangeline_lilly_brie	8	[]
1	t1_ghuwup4	/r/CelebBattles/comments/kp2qmx/rachel_mcadams...	Rachel	t3_kp2qmx	r/CelebBattles	gaul66	2021-01-02 20:16:31	Neutral	Neutral	2.0	submission	comment	1	rachel_mcadams_vs_amber_heard	5	[]
2	t1_giqmms5	/r/CelebBattles/comments/ku6peu/hotter_one_gal...	Gal	t3_ku6peu	r/CelebBattles	gaul66	2021-01-10 06:10:19	Neutral	Neutral	5.0	submission	comment	1	hotter_one_gal_gadot_vs_amber_heard_vs_alison_...	10	[]
3	t1_gk1f28y	/r/CelebBattles/comments/l1qwsh/my_top_6random...	Natalie	t3_l1qwsh	r/CelebBattles	gaul66	2021-01-21 07:10:16	Neutral	Neutral	1.0	submission	comment	1	my_top_6random_order_natalie_portman_vs_emily	8	[]
4	t1_gkf1t2n	/r/CelebBattles/comments/l3eo1l/katy_perry_vs_...	Evangeline	t3_l3eo1l	r/CelebBattles	gaul66	2021-01-23 18:03:01	Neutral	Neutral	2.0	submission	comment	1	katy_perry_vs_evangeline_lilly_vs_amber_heard	8	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t3_kul0ox	/r/celebgifs/comments/kul0ox/amber_heard_enjoy...	Amber Heard enjoying some entertainment	NaN	r/celebgifs	LoveAmberHeard42286	2021-01-10 19:31:39	Positive	Positive	0.0	NaN	submission	5	amber_heard_enjoying_some_entertainment	5	[]
1	t1_gishb5o	/r/gentlemanboners/comments/kffqt2/amber_heard...	Stunning	t3_kffqt2	r/gentlemanboners	LoveAmberHeard42286	2021-01-10 19:36:30	Positive	Positive	3.0	submission	comment	1	amber_heard	2	[]
2	t3_kul5v4	/r/gentlemanboners/comments/kul5v4/amber_heard/	Amber Heard	NaN	r/gentlemanboners	LoveAmberHeard42286	2021-01-10 19:38:05	Neutral	Neutral	0.0	NaN	submission	2	amber_heard	2	[]
3	t1_gismviy	/r/unpopularopinion/comments/jps1eu/johnny_dep...	He did. Hence why he lost his case. They had r...	t3_jps1eu	r/unpopularopinion	LoveAmberHeard42286	2021-01-10 20:22:23	Negative	Negative	2.0	submission	comment	59	johnny_depp_probably_did_physically_abuse_amber	7	[]
4	t1_gisn0sb	/r/unpopularopinion/comments/ht1ota/amber_hear...	... 5 months later. Looks like the sun wasn't ...	t3_ht1ota	r/unpopularopinion	LoveAmberHeard42286	2021-01-10 20:23:33	Neutral	Positive	2.0	submission	comment	12	amber_heard_and_johnny_depp_both_suck	7	[]

	created_at	n_contributions
17	2021-03-15	9
11	2021-03-08	8
16	2021-03-14	7
33	2021-05-02	7
24	2021-04-14	7
23	2021-04-03	5
0	2021-01-10	5
27	2021-04-22	5
6	2021-02-27	4
12	2021-03-09	4
18	2021-03-16	4
28	2021-04-23	3
26	2021-04-21	3
29	2021-04-24	3
30	2021-04-28	3
31	2021-04-29	3
19	2021-03-28	3
42	2021-05-31	3
9	2021-03-04	3
15	2021-03-13	2
8	2021-03-03	2
40	2021-05-26	2
38	2021-05-13	2
37	2021-05-11	2
2	2021-02-19	2
3	2021-02-20	2
7	2021-03-02	2
4	2021-02-23	2
25	2021-04-19	2
20	2021-03-29	2
5	2021-02-24	1
14	2021-03-11	1
10	2021-03-07	1
32	2021-04-30	1
13	2021-03-10	1
34	2021-05-04	1
35	2021-05-09	1
36	2021-05-10	1
22	2021-04-01	1
1	2021-01-20	1
39	2021-05-20	1
41	2021-05-27	1
21	2021-03-31	1

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t1_gxpnlsu	/r/pussypassdenied/comments/n95rfx/amber_heard...	Good... \n\n"" He said: “The severity of these...	t3_n95rfx	r/pussypassdenied	sadwook	2021-05-11 10:09:06	Positive	Negative	1.0	submission	comment	101	amber_heard_to_struggle_in_new_lapd_domestic	8	[]
1	t1_gxpnp4c	/r/pussypassdenied/comments/n95rfx/amber_heard...	i will not hold back. JUSTICE FOR JOHNNY	t3_n95rfx	r/pussypassdenied	sadwook	2021-05-11 10:10:29	Neutral	Negative	2.0	submission	comment	8	amber_heard_to_struggle_in_new_lapd_domestic	8	[]
2	t1_gxpntzg	/r/pussypassdenied/comments/n95rfx/amber_heard...	we wont stay silent. this mans reputation is g...	t1_gxnoecm	r/pussypassdenied	sadwook	2021-05-11 10:12:32	Positive	Neutral	1.0	comment	comment	34	amber_heard_to_struggle_in_new_lapd_domestic	8	[]
3	t1_gxpnxf1	/r/pussypassdenied/comments/n95rfx/amber_heard...	pretty much the summary of her career. im not ...	t1_gxoh4o0	r/pussypassdenied	sadwook	2021-05-11 10:13:55	Negative	Neutral	3.0	comment	comment	24	amber_heard_to_struggle_in_new_lapd_domestic	8	[]
4	t1_gxpnzbf	/r/pussypassdenied/comments/n95rfx/amber_heard...	bruh	t1_gxn7p1k	r/pussypassdenied	sadwook	2021-05-11 10:14:43	Neutral	Neutral	0.0	comment	comment	1	amber_heard_to_struggle_in_new_lapd_domestic	8	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
0	t1_gpl1ocz	/r/TrueOffMyChest/comments/lx2s7w/its_disgusti...	Wait wait. Has something changed here. Because...	t3_lx2s7w	r/TrueOffMyChest	Beatplayer	2021-03-03 22:00:23	Negative	Neutral	36.0	submission	comment	36	its_disgusting_that_people_are_less_angry_about	8	[]
1	t1_gpl5mw9	/r/TrueOffMyChest/comments/lx2s7w/its_disgusti...	But then again, that was just a statement made...	t1_gpl5997	r/TrueOffMyChest	Beatplayer	2021-03-03 22:30:38	Positive	Neutral	-1.0	comment	comment	86	its_disgusting_that_people_are_less_angry_about	8	[]
2	t1_gpl71q8	/r/TrueOffMyChest/comments/lx2s7w/its_disgusti...	Like most abusive relationships tbh, from the ...	t1_gpl6uww	r/TrueOffMyChest	Beatplayer	2021-03-03 22:41:44	Positive	Neutral	-2.0	comment	comment	26	its_disgusting_that_people_are_less_angry_about	8	[]
3	t1_gpla7k5	/r/TrueOffMyChest/comments/lx2s7w/its_disgusti...	K. So I’m 12.5 mins in, and absolutely shatter...	t1_gpl8d57	r/TrueOffMyChest	Beatplayer	2021-03-03 23:07:01	Negative	Negative	20.0	comment	comment	109	its_disgusting_that_people_are_less_angry_about	8	[]
4	t1_gplbi77	/r/TrueOffMyChest/comments/lx2s7w/its_disgusti...	I’m not sure that the case to be honest. \n\nI...	t1_gpl9u5x	r/TrueOffMyChest	Beatplayer	2021-03-03 23:17:45	Negative	Neutral	15.0	comment	comment	149	its_disgusting_that_people_are_less_angry_about	8	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
4432	AutoModerator	True	True	True	False	1000.0	1000.0	2012-01-05 05:24:28	others	others
8326	faithle55	True	False	False	False	328449.0	482.0	2013-01-06 22:13:46	others	others

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
54	t1_gho9bpc	/r/CelebBattles/comments/ko1duk/marvel_vs_dc_t...	Fuck a nd I thought I didn't have a life LOL	t1_gho5bap	r/CelebBattles	Beav365	2021-01-01 03:57:09	Positive	Negative	-2.0	comment	comment	11	marvel_vs_dc_team_marvel_evangeline_lilly_brie	8	[]
88	t1_ghoms5q	/r/redditmoment/comments/ko1xfy/delete_tik_tok...	Shut the fuck up about this stealing your priv...	t1_ghoe5zj	r/redditmoment	big-shaq-skrra	2021-01-01 06:54:36	Negative	Negative	56.0	comment	comment	28	delete_tik_tok_or_slap_amber_heard	7	[]
105	t1_ghooy78	/r/redditmoment/comments/ko1xfy/delete_tik_tok...	What the fuck	t1_ghon57f	r/redditmoment	Bombz_Armed	2021-01-01 07:28:39	Negative	Negative	55.0	comment	comment	3	delete_tik_tok_or_slap_amber_heard	7	[]
110	t1_ghopc1o	/r/Teenager/comments/knh0wt/just_cuz_i_wanna_k...	who the fuck voted ofr amber heard	t3_knh0wt	r/Teenager	matthew35433ma	2021-01-01 07:34:53	Negative	Negative	1.0	submission	comment	7	just_cuz_i_wanna_know_how_many_of_you_support	10	[]
142	t1_ghot913	/r/redditmoment/comments/ko1xfy/delete_tik_tok...	I'd fuck her for sure	t3_ko1xfy	r/redditmoment	FatHandNoticer	2021-01-01 08:45:21	Positive	Neutral	-11.0	submission	comment	5	delete_tik_tok_or_slap_amber_heard	7	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
684	t3_kpbsbr	/r/Animemes/comments/kpbsbr/fuck_amber_heard/	Fuck amber heard	NaN	r/Animemes	dingusbob69	2021-01-03 02:38:42	Negative	Negative	269.0	NaN	submission	3	fuck_amber_heard	3	[]
889	t3_kq9lal	/r/memes/comments/kq9lal/fuck_amber_heard/	fuck Amber Heard	NaN	r/memes	guyinAmerica1	2021-01-04 14:18:40	Negative	Negative	1.0	NaN	submission	3	fuck_amber_heard	3	[]
1404	t3_kriljq	/r/JusticeForJohnnyDepp/comments/kriljq/fuck_amber_heard/	fuck amber heard	NaN	r/JusticeForJohnnyDepp	isaac0304	2021-01-06 06:59:05	Negative	Negative	33.0	NaN	submission	3	fuck_amber_heard	3	[]
1853	t3_ktkm8u	/r/EntitledBitch/comments/ktkm8u/fuck_amber_heard/	Fuck amber heard	NaN	r/EntitledBitch	big_pog_human2478	2021-01-09 05:17:34	Negative	Negative	14738.0	NaN	submission	3	fuck_amber_heard	3	[]
2389	t3_kukxmy	/r/SupportAmberHeard/comments/kukxmy/fuck_amber_heard/	FUCK AMBER HEARD	NaN	r/SupportAmberHeard	Flerp6969	2021-01-10 19:28:00	Negative	Negative	54.0	NaN	submission	3	fuck_amber_heard	3	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
183	t3_ko9ymn	/r/memes/comments/ko9ymn/fuck_amber_heard_credit_to_uwhitewolf699420_for/	Fuck Amber Heard (credit to u/Whitewolf699420 for the template)	NaN	r/memes	-banned-	2021-01-01 11:39:40	Negative	Negative	1.0	NaN	submission	9	fuck_amber_heard_credit_to_uwhitewolf699420_for	7	[]
186	t3_ko9zmj	/r/dankmemes/comments/ko9zmj/fuck_amber_heard_credit_to_uwhitewolf699420_for/	Fuck Amber Heard (credit to u/Whitewolf699420 for template)	NaN	r/dankmemes	-banned-	2021-01-01 11:41:46	Negative	Negative	1.0	NaN	submission	8	fuck_amber_heard_credit_to_uwhitewolf699420_for	7	[]
684	t3_kpbsbr	/r/Animemes/comments/kpbsbr/fuck_amber_heard/	Fuck amber heard	NaN	r/Animemes	dingusbob69	2021-01-03 02:38:42	Negative	Negative	269.0	NaN	submission	3	fuck_amber_heard	3	[]
889	t3_kq9lal	/r/memes/comments/kq9lal/fuck_amber_heard/	fuck Amber Heard	NaN	r/memes	guyinAmerica1	2021-01-04 14:18:40	Negative	Negative	1.0	NaN	submission	3	fuck_amber_heard	3	[]
1404	t3_kriljq	/r/JusticeForJohnnyDepp/comments/kriljq/fuck_amber_heard/	fuck amber heard	NaN	r/JusticeForJohnnyDepp	isaac0304	2021-01-06 06:59:05	Negative	Negative	33.0	NaN	submission	3	fuck_amber_heard	3	[]

	created_at	n_contributions
24	2021-03-29	4
6	2021-01-10	3
0	2021-01-01	2
14	2021-02-01	2
27	2021-04-14	2
26	2021-04-08	2
23	2021-03-28	2
19	2021-03-05	2
34	2021-05-19	2
8	2021-01-16	2
7	2021-01-13	2
9	2021-01-18	1
5	2021-01-09	1
33	2021-05-07	1
32	2021-04-29	1
31	2021-04-27	1
30	2021-04-23	1
29	2021-04-22	1
28	2021-04-15	1
2	2021-01-04	1
3	2021-01-06	1
25	2021-04-01	1
4	2021-01-07	1
22	2021-03-13	1
10	2021-01-20	1
21	2021-03-10	1
20	2021-03-08	1
18	2021-02-22	1
1	2021-01-03	1
16	2021-02-12	1
15	2021-02-09	1
13	2021-01-30	1
12	2021-01-29	1
11	2021-01-28	1
17	2021-02-18	1

	created_at	n_contributions
92	2021-04-17	73
54	2021-02-28	72
58	2021-03-04	60
115	2021-05-11	45
46	2021-02-20	40
15	2021-01-16	34
112	2021-05-08	25
93	2021-04-18	25
81	2021-04-01	24
0	2021-01-01	23

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
13069	t1_guu4ilo	/r/entertainment/comments/msgoz8/johnny_depp_r...	She was feeding him Xanax constantly too, you ...	t1_gutc2jp	r/entertainment	Jreal22	2021-04-17 11:43:17	Negative	Neutral	60.0	comment	comment	76	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
13073	t1_guu4sfw	/r/entertainment/comments/msgoz8/johnny_depp_r...	Lots of people have their lines fed to them, i...	t1_gutd28y	r/entertainment	Jreal22	2021-04-17 11:45:13	Negative	Negative	6.0	comment	comment	49	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
13076	t1_guu57ix	/r/entertainment/comments/msgoz8/johnny_depp_r...	Yeah, I couldn't believe this.\n\nThey tried t...	t1_guthn8f	r/entertainment	Jreal22	2021-04-17 11:48:22	Positive	Neutral	23.0	comment	comment	58	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
13081	t1_guu60bw	/r/entertainment/comments/msgoz8/johnny_depp_r...	Yeah, Depp needed to stop doing the same movie...	t1_guteoj8	r/entertainment	Jreal22	2021-04-17 11:54:07	Positive	Positive	1.0	comment	comment	36	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
13092	t1_guu7wa8	/r/entertainment/comments/msgoz8/johnny_depp_r...	Jay Z should have taken Chris brown out back a...	t1_gutexk2	r/entertainment	Jreal22	2021-04-17 12:07:33	Negative	Neutral	8.0	comment	comment	39	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
64297	RoleplayGuy21	False	True	False	False	1627.0	26569.0	2020-11-06 18:10:49	unverified	2020
65499	RoleplayTime21	False	False	False	False	220.0	1188.0	2021-04-14 11:10:20	unverified	2021

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
107	t1_ghop7t4	/r/redditmoment/comments/ko1xfy/delete_tik_tok_or_slap_amber_heard/ghop7t4/	guys amber heard bad now give me upvotes	t3_ko1xfy	r/redditmoment	LupLush	2021-01-01 07:32:58	Negative	Negative	6.0	submission	comment	8	delete_tik_tok_or_slap_amber_heard	7	[]
199	t1_ghpdwee	/r/redditmoment/comments/ko1xfy/delete_tik_tok_or_slap_amber_heard/ghpdwee/	Because there's such a weird fixation on this one instance of abuse. It feels like they don't hate on abusers but on Amber Heard specifically. There was a post on madlads recently where someone was called "madlad" for posting "Amber Heard bad" on her subreddit.\n\nAnd let's face it, this is only because she is a prominent case of a female abuser, if she were male she would be hated but nowhere near the degree she is now, and people would throw around claims of false accusations.	t1_ghoztk6	r/redditmoment	HardcoreTristesse	2021-01-01 12:27:12	Negative	Neutral	2.0	comment	comment	87	delete_tik_tok_or_slap_amber_heard	7	[]
551	t1_ghth3rk	/r/Amber_Heard/comments/klcvt6/lol_amber_heard_bad/ghth3rk/	Yes, amber heard bad	t3_klcvt6	r/Amber_Heard	Affectionate-Ad-2630	2021-01-02 11:12:57	Negative	Neutral	1.0	submission	comment	4	Amber_Heard	2	[]
954	t3_kqfpmi	/r/PewdiepieSubmissions/comments/kqfpmi/amber_heard_bad/	Amber Heard bad	NaN	r/PewdiepieSubmissions	Raven_Force	2021-01-04 19:22:03	Negative	Negative	1.0	NaN	submission	3	amber_heard_bad	3	[]
1006	t3_kqosqs	/r/memes/comments/kqosqs/amber_heard_bad/	Amber heard bad	NaN	r/memes	-banned-	2021-01-05 02:52:16	Negative	Negative	1.0	NaN	submission	3	amber_heard_bad	3	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
21296	YourMotherSaysHello	True	False	False	False	246346.0	8947.0	2016-01-22 16:05:21	others	others
25031	oldmanjenkins51	False	False	False	False	18274.0	25907.0	2016-09-16 15:38:57	unverified	others
31420	KthulhuX	True	True	False	False	60055.0	4839.0	2017-08-24 19:04:43	others	others
47692	bradje61	True	False	False	False	502.0	22828.0	2019-04-27 09:01:11	others	2019
49465	dansonquack	True	True	True	False	4748.0	54495.0	2019-06-22 11:26:46	others	2019
51861	LupLush	True	True	False	False	3054.0	27271.0	2019-09-02 17:22:19	others	2019
53243	HardcoreTristesse	True	False	False	False	10099.0	1352.0	2019-10-18 10:22:06	others	2019
53906	Sadclocktowernoises	True	False	False	False	9199.0	1212.0	2019-11-08 16:04:34	others	2019
56762	SamGamer012	True	True	False	False	17070.0	10489.0	2020-01-30 09:31:35	others	2020
56916	Memelord96024	True	False	False	False	308.0	6790.0	2020-02-02 20:21:28	others	2020
59969	skyrise011	True	False	False	False	335.0	623.0	2020-05-20 13:37:53	others	2020
60607	DuplicateDestroyer	True	True	False	False	81.0	111.0	2020-06-13 02:32:27	others	2020
61003	ReShout876	True	True	False	False	2648.0	6120.0	2020-06-27 19:55:09	others	2020
61302	Raven_Force	True	False	False	False	64.0	1004.0	2020-07-07 22:06:13	others	2020
61746	Affectionate-Ad-2630	True	False	False	False	5.0	1.0	2020-07-25 10:45:26	others	2020
64662	Most-Programmer-1046	True	False	False	False	40.0	682.0	2020-11-27 18:36:16	others	2020
64998	Lolthisistrash1234	True	True	False	False	2513.0	15701.0	2020-12-29 03:18:45	others	2020
70249	buwud	True	True	True	True	NaN	NaN	NaT	banned	banned

Case Study: Reddit Social Network Analysis Against Influence Operation¶

Table of Contents¶

Introduction¶

Exploratory Data Analysis¶

Reddit Contributions (Comments / Submissions)¶

The # of submissions VS the # of comments¶

Most contributed user¶

Further Investigate The Most Commented Users In 2021¶

AutoModerator¶

CelebBattleVoteBot¶

charliedba¶

Stanley_Elkind¶

Truthbetheprejudice¶

gaul66¶

sadwook¶

Beatplayer¶

Check wether the users with the most contributions are mod, gold or having a verified email¶

Investigate the text column¶

Investigate The Most Negative key Words Used (from the wordcloud map)¶

Lets first check for the users using the word 'f*ck'¶

Jreal22¶

Check for the repeated text¶

can somebody rp as amber heard for me longterm¶

amber heard bad¶

F*ck amber heard¶

good bot¶

Amber Heard Touching Herself¶

Amber Heard in Aquaman 2, why?¶

Further check Lecrapface contributions on 2021¶

Check the number of text words

Reddit Comments¶

The number of parent comments on submissions¶

Reddit Submission Data¶

Investigating the Submission Text (Submissions with the most comments and replies)

emilia_clarke_to_replace_amber_heard_as_mera_in¶

amber_heard_has_been_fired_from_jason_momoas¶

johnny_depp_releases_lapd_bodycam_footage_proving¶

Invesigating the sumbissions with most comments (Top Level Comments)

Check the top 5 submissions in 2021¶

Define a function to create the mask and check if a submission text is part of the top 5 submissions¶

Check the authors of parent comments¶

Invesigating authors with the most submissions¶

Let us first Investigate authors with the most submissions¶

Check wether the users with the most submissions are mod, gold or having a verified email¶

Submission URLS¶

Check the number of submission text words

Subredits¶

Most used Subreddits¶

Merged Users Data with Comments & Submissions Data¶

Difference in time between creating the account and posting¶

Posting Duration After Account Creation¶

THE SAME MONTH:¶

THE SAME WEEK¶

THE SAME DAY¶

Estimation of Number of User Accounts Created in each year / having contributions in 2021¶

Peaks¶

Contributions count over Months in 2021¶

Contributions count over Days of month in 2021¶

In Which DayOfWeek users created more?¶

check for the hour the contributions were made (2021)¶

Which dates has the highest contrbitions for users?¶

How many users contributed on the peak day (Apr 17,2021)¶

And From What Years?¶

check for the hour the contributions were made on the peak day (Apr 17,2021)¶

How many users contributed on the peak day (Feb 20,2021)¶

And From What Years?¶

check for the hour the contributions were made on the peak day (Feb 20,2021)¶

How many users contributed on the peak day (Feb 28,2021)¶

And From What Years?¶

check for the hour the contributions were made on the peak day (Feb 28,2021)¶

Conclusions¶

Investigating the Submission Text
(Submissions with the most comments and replies)

Invesigating the sumbissions with most comments
(Top Level Comments)

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
1937	t1_ginfp9p	/r/EntitledBitch/comments/ktkm8u/fuck_amber_heard/ginfp9p/	Good bot	t1_ginev86	r/EntitledBitch	chixnwafflez	2021-01-09 12:40:12	Positive	Positive	6.0	comment	comment	2	fuck_amber_heard	3	[]
5216	t1_glpyfc4	/r/MensRights/comments/lac30r/you_saved_me_johnny_depp_thanks_supporters_for/glpyfc4/	Good bot	t1_glpye3x	r/MensRights	Amazing-Row-5963	2021-02-02 11:58:38	Positive	Positive	1.0	comment	comment	2	you_saved_me_johnny_depp_thanks_supporters_for	8	[]
5748	t1_gmsoxjj	/r/MensRights/comments/lgbi6k/amber_heard_reportedly_in_talks_for_star_wars_role/gmsoxjj/	Good bot	t1_gmrdo94	r/MensRights	Icr711	2021-02-10 08:15:09	Positive	Positive	2.0	comment	comment	2	amber_heard_reportedly_in_talks_for_star_wars_role	9	[]
5798	t1_gmu3sk1	/r/MensRights/comments/lgbi6k/amber_heard_reportedly_in_talks_for_star_wars_role/gmu3sk1/	Good bot, boy!	t1_gmrdo94	r/MensRights	loucos3	2021-02-10 17:10:37	Positive	Positive	1.0	comment	comment	3	amber_heard_reportedly_in_talks_for_star_wars_role	9	[]
8736	t1_gp58cvf	/r/pussypassdenied/comments/lu5055/amber_heard_has_been_fired_from_jason_momoas/gp58cvf/	Good bot	t1_gp51cwx	r/pussypassdenied	RunningBread888_yt	2021-02-28 08:04:04	Positive	Positive	17.0	comment	comment	2	amber_heard_has_been_fired_from_jason_momoas	8	[]

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls	urls_count
70	t1_ghogbmf	/r/memes/comments/ko5qc9/apkngxpraw_now_theres_the_meeting_code_do_what/ghogbmf/	Hello /u/thatgamerguy567! Unfortunately, your post has been removed. To protect the subreddit from advertising spam, ban evasions and abuse, we no longer allow new/inactive users to make submissions, you need to build up some post, comment karma and history. In the mean time, please be sure to familiarize yourself with our subreddit rules:\n \n>/r/memes/about/rules\n>\n>r/memes/about/sidebar\n\nIn order to achieve the threshold, we ask you to post to other subs around Reddit, and contribute in comments to build up your post and comment karma. You can hover over your karma on your profile to see the difference between post and comment karma, as we do not evaluate your overall karma. This may explain why you often see someone with "lower" overall karma able to post. You are welcome to comment in r/memes in order to spend some time getting to know our community, then you'll be welcome to make submissions.\n\n1\. No, the bot did not make a mistake. The bot is excellent at counting.\n\n2\. When the bot stops removing your posts, you'll know that you've finally met our requirements.\n\n3\. We will not tell you how much karma you need.\n\nThanks for understanding.\n\n---\n\n#Please do not message us about this, we need the minimum karma filter to prevent spam. Thank you\n\n---\n\n\nI am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/memes) if you have any questions or concerns.	t3_ko5qc9	r/memes	AutoModerator	2021-01-01 05:25:21	Positive	Neutral	1.0	submission	comment	239	apkngxpraw_now_theres_the_meeting_code_do_what	8	[]	0
260	t1_ghq4xri	/r/meme/comments/kodofd/roles_perfect_for_amber_heard/ghq4xri/	Hey!\n\nYou've submitted an uncropped image.\n\n[Click here](https://lmgtfy.com/?q=how+to+crop+an+image&s=g) to learn how to crop an image.\n\nOnce you've cropped the image properly, you may resubmit it.\n\nThanks!\n\n-----------------------\n\nI'm a bot so if I was wrong, reply to me and a moderator will check it.	t3_kodofd	r/meme	MAGIC_EYE_BOT	2021-01-01 16:08:52	Negative	Neutral	0.0	submission	comment	44	roles_perfect_for_amber_heard	5	['https://lmgtfy.com']	1
399	t1_ghrcepj	/r/Makeup/comments/kogfek/amber_heard_the_face_of_new_loréal_ad_after/ghrcepj/	The Hollywood Reporter had a really interesting article on Depp. Apparently he has a very toxic fan base/lots of bot supporters. \n\nhttps://www.hollywoodreporter.com/features/hes-radioactive-inside-johnny-depps-self-made-implosion	t1_ghra7an	r/Makeup	SwimmingCoyote	2021-01-01 20:58:43	Positive	Positive	25.0	comment	comment	22	amber_heard_the_face_of_new_loréal_ad_after	9	['https://www.hollywoodreporter.com']	1
723	t1_ghxjsqp	/r/Animemes/comments/kpbsbr/fuck_amber_heard/ghxjsqp/	This submission was removed for breaking Rule 9: Be Nice.\n\n--- \n\nI am a bot and this comment was made automatically. However, this submission was removed manually by a member of the mod team. If you have questions or concerns about this removal, please contact the moderators through modmail.	t3_kpbsbr	r/Animemes	AnimemesBot	2021-01-03 10:11:12	Positive	Positive	1.0	submission	comment	49	fuck_amber_heard	3	[]	0
1064	t1_gi619f9	/r/memes/comments/kqvoqr/help_soldier_this_for_some_reason_has_hate/gi619f9/	Hello /u/cat_t_cat! Unfortunately, your post has been removed. To protect the subreddit from advertising spam, ban evasions and abuse, we no longer allow new/inactive users to make submissions, you need to build up some post, comment karma and history. In the mean time, please be sure to familiarize yourself with our subreddit rules:\n \n>/r/memes/about/rules\n>\n>r/memes/about/sidebar\n\nIn order to achieve the threshold, we ask you to post to other subs around Reddit, and contribute in comments to build up your post and comment karma. You can hover over your karma on your profile to see the difference between post and comment karma, as we do not evaluate your overall karma. This may explain why you often see someone with "lower" overall karma able to post. You are welcome to comment in r/memes in order to spend some time getting to know our community, then you'll be welcome to make submissions.\n\n1\. No, the bot did not make a mistake. The bot is excellent at counting.\n\n2\. When the bot stops removing your posts, you'll know that you've finally met our requirements.\n\n3\. We will not tell you how much karma you need.\n\nThanks for understanding.\n\n---\n\n#Please do not message us about this, we need the minimum karma filter to prevent spam. Thank you\n\n---\n\n\nI am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/memes) if you have any questions or concerns.	t3_kqvoqr	r/memes	AutoModerator	2021-01-05 10:18:57	Positive	Neutral	1.0	submission	comment	239	help_soldier_this_for_some_reason_has_hate	8	[]	0

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	top_level	submission_comment	text_words	submission_text	submission_words	urls
12416	t3_mqpbo7	/r/dekaihentai/comments/mqpbo7/amber_heard_tou...	Amber Heard Touching Herself	NaN	r/dekaihentai	owenlinx	2021-04-14 12:17:01	Positive	Neutral	NaN	submission	4	amber_heard_touching_herself	4	[]
12417	t3_mqpbp7	/r/chastity/comments/mqpbp7/amber_heard_touchi...	Amber Heard Touching Herself	NaN	r/chastity	owenlinx	2021-04-14 12:17:03	Positive	Neutral	NaN	submission	4	amber_heard_touching_herself	4	[]
12418	t3_mqpbq4	/r/1819club/comments/mqpbq4/amber_heard_touchi...	Amber Heard Touching Herself	NaN	r/1819club	owenlinx	2021-04-14 12:17:06	Positive	Neutral	NaN	submission	4	amber_heard_touching_herself	4	[]
12419	t3_mqpbqi	/r/Nekomimi/comments/mqpbqi/amber_heard_touchi...	Amber Heard Touching Herself	NaN	r/Nekomimi	owenlinx	2021-04-14 12:17:06	Positive	Neutral	NaN	submission	4	amber_heard_touching_herself	4	[]
12420	t3_mqpbro	/r/SideLips/comments/mqpbro/amber_heard_touchi...	Amber Heard Touching Herself	NaN	r/SideLips	owenlinx	2021-04-14 12:17:09	Positive	Neutral	NaN	submission	4	amber_heard_touching_herself	4	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
26514	garretdanielkelly	False	False	False	False	1061.0	1.0	2016-12-12 03:40:01	unverified	others
43427	owenlinx	False	True	False	False	11983.0	5153.0	2019-01-01 09:15:33	unverified	2019
70432	90police	True	True	True	True	NaN	NaN	NaT	banned	banned

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
4677	t1_glcu8wu	/r/pussypassdenied/comments/k09s59/the_petitio...	Here's what I did, repost from another subredd...	t3_k09s59	r/pussypassdenied	Lecrapface	2021-01-30 10:40:26	Negative	Neutral	1.0	submission	comment	140	the_petition_to_fire_amber_heard_from_aquaman_2	9	[]
4687	t1_glcvob6	/r/DC_Movies/comments/k4s16h/amber_heard_aquam...	This is what I did\n\n Well I'm going to start...	t3_k4s16h	r/DC_Movies	Lecrapface	2021-01-30 11:03:11	Negative	Neutral	1.0	submission	comment	137	DC_Movies	2	[]
4689	t1_glcvp7g	/r/CosmicBookNews/comments/k4s159/amber_heard_...	Well I'm going to start doing preliminary emai...	t3_k4s159	r/CosmicBookNews	Lecrapface	2021-01-30 11:03:34	Negative	Neutral	1.0	submission	comment	132	amber_heard_aquaman_2_petition_over_16_million	8	[]
4690	t1_glcvrnt	/r/boxoffice/comments/k336a3/petition_to_axe_a...	Well I'm going to start doing preliminary emai...	t3_k336a3	r/boxoffice	Lecrapface	2021-01-30 11:04:39	Negative	Neutral	1.0	submission	comment	132	petition_to_axe_amber_heard_from_aquaman_2	8	[]
4691	t1_glcvsxj	/r/DC_Cinematic/comments/k336ef/article_petiti...	Well I'm going to start doing preliminary emai...	t3_k336ef	r/DC_Cinematic	Lecrapface	2021-01-30 11:05:12	Negative	Neutral	1.0	submission	comment	132	DC_Cinematic	2	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
4654	UltraMagnus0001	True	False	False	False	51696.0	18214.0	2012-01-25 22:06:22	others	others
47731	Watcher2020	True	False	False	False	123.0	56960.0	2019-04-28 20:55:03	others	2019
60311	UnHope20	False	True	False	False	4497.0	8588.0	2020-06-01 20:46:13	unverified	2020

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
8565	t3_lu1659	/r/byebyejob/comments/lu1659/amber_heard_has_been_fired_from_jason_momoas/	Amber Heard Has Been Fired From Jason Momoa's "Aquaman 2"	NaN	r/byebyejob	ToyaW31	2021-02-28 00:31:48	Neutral	Negative	1.0	NaN	submission	10	amber_heard_has_been_fired_from_jason_momoas	8	[]
8585	t3_lu5055	/r/pussypassdenied/comments/lu5055/amber_heard_has_been_fired_from_jason_momoas/	Amber Heard Has Been Fired From Jason Momoa's "Aquaman 2"	NaN	r/pussypassdenied	MahatmaGandamnit	2021-02-28 03:51:34	Neutral	Negative	29511.0	NaN	submission	10	amber_heard_has_been_fired_from_jason_momoas	8	[]
8588	t3_lu587o	/r/byebyejob/comments/lu587o/amber_heard_has_been_fired_from_jason_momoas/	Amber Heard Has Been Fired From Jason Momoa's "Aquaman 2"	NaN	r/byebyejob	Weezy-NJPW_Fan	2021-02-28 03:59:39	Neutral	Negative	1.0	NaN	submission	10	amber_heard_has_been_fired_from_jason_momoas	8	[]
9586	t3_lwihhx	/r/MensRights/comments/lwihhx/amber_heard_has_been_fired_from_jason_momoas/	Amber Heard Has Been Fired From Jason Momoa's "Aquaman 2": Report	NaN	r/MensRights	PeonSupreme	2021-03-03 02:02:38	Neutral	Negative	1.0	NaN	submission	11	amber_heard_has_been_fired_from_jason_momoas	8	[]

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
25395	MahatmaGandamnit	True	False	False	False	7219.0	10995.0	2016-10-10 00:01:25	others	others
34393	PeonSupreme	True	True	False	False	39131.0	137125.0	2018-01-24 19:00:30	others	2018
49236	ToyaW31	True	False	False	False	1133.0	2899.0	2019-06-14 23:05:24	others	2019
61898	Weezy-NJPW_Fan	True	False	True	False	911523.0	1940933.0	2020-07-31 02:27:31	others	2020

	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year
4713	autotldr	True	True	False	False	2752068.0	286509.0	2012-01-30 16:39:40	others	others
25954	Gato1980	True	False	True	False	440406.0	1591399.0	2016-11-12 21:45:46	others	others
70420	Danger3214	True	True	True	True	NaN	NaN	NaT	banned	banned

	child_id	permalink	text	parent_id	subreddit	author	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	text_words	submission_text	submission_words	urls
12654	t3_msgoz8	/r/entertainment/comments/msgoz8/johnny_depp_r...	Johnny Depp releases LAPD bodycam footage prov...	NaN	r/entertainment	Gato1980	2021-04-17 00:54:16	Neutral	Negative	15660.0	NaN	submission	17	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
12655	t1_gusgmjz	/r/entertainment/comments/msgoz8/johnny_depp_r...	[deleted]	t3_msgoz8	r/entertainment	-banned-	2021-04-17 00:56:13	Neutral	Neutral	-14.0	submission	comment	1	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
12656	t3_msgtce	/r/autotldr/comments/msgtce/johnny_depp_releas...	Johnny Depp releases LAPD bodycam footage prov...	NaN	r/autotldr	autotldr	2021-04-17 01:01:41	Neutral	Negative	65.0	NaN	submission	17	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
12658	t1_gusigwx	/r/entertainment/comments/msgoz8/johnny_depp_r...	[deleted]	t3_msgoz8	r/entertainment	-banned-	2021-04-17 01:13:03	Neutral	Neutral	-70.0	submission	comment	1	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]
12659	t1_guslddq	/r/entertainment/comments/msgoz8/johnny_depp_r...	Who cares about his career. Let the truth come...	t1_gusgmjz	r/entertainment	Temporary_Draw_4708	2021-04-17 01:39:22	Neutral	Positive	13.0	comment	comment	10	johnny_depp_releases_lapd_bodycam_footage_proving	7	[]